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Proceedings ArticleDOI

Multiobjective Optimization of FPGA-Based Medical Image Registration

14 Apr 2008-pp 183-192

TL;DR: This paper presents a multiobjective optimization strategy developed in the context of field-programmable gate array-based implementation of medical image registration that can easily be adapted to a wide range of signal processing applications, including areas of image and video processing beyond the medical domain.
Abstract: With a multitude of technological innovations, one emerging trend in image processing, and medical image processing, in particular, is custom hardware implementation of computationally intensive algorithms in the quest to achieve real-time performance. For reasons of area-efficiency and performance, these implementations often employ limited-precision datapaths. Identifying effective wordlengths for these datapaths while accounting for tradeoffs between design complexity and accuracy is a critical and time consuming aspect of this design process. Having access to optimized tradeoff curves can equip designers to adapt their designs to different performance requirements and target specific devices while reducing design time. This paper presents a multiobjective optimization strategy developed in the context of field-programmable gate array-based implementation of medical image registration. Within this framework, we compare several search methods and demonstrate the applicability of an evolutionary algorithm-based search for efficiently identifying superior multiobjective tradeoff curves. This strategy can easily be adapted to a wide range of signal processing applications, including areas of image and video processing beyond the medical domain.

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Multiobjective Optimization of FPGA-Based Medical Image Registration
Omkar Dandekar
1,2
, William Plishker
1,2
,
Shuvra Bhattacharyya
1
1
Department of Electrical and Computer Engineering,
University of Maryland,
College Park, MD 20742
{omkar, plishker, ssb}@umd.edu
Raj Shekhar
1,2
2
Department of Diagnostic Radiology,
University of Maryland,
Baltimore, MD 21201
rshekhar@umm.edu
Abstract
With a multitude of technological innovations, one
emerging trend in image processing, and medical image
processing, in particular, is custom hardware
implementation of computationally intensive algorithms in
the quest to achieve real-time performance. For reasons of
area-efficiency and performance, these implementations
often employ limited-precision datapaths. Identifying
effective wordlengths for these datapaths while accounting
for tradeoffs between design complexity and accuracy is a
critical and time consuming aspect of this design process.
Having access to optimized tradeoff curves can equip
designers to adapt their designs to different performance
requirements and target specific devices while reducing
design time. This paper presents a multiobjective
optimization strategy developed in the context of field-
programmable gate array–based implementation of
medical image registration. Within this framework, we
compare several search methods and demonstrate the
applicability of an evolutionary algorithm–based search
for efficiently identifying superior multiobjective tradeoff
curves. This strategy can easily be adapted to a wide
range of signal processing applications, including areas
of image and video processing beyond the medical
domain.
1. Introduction
An emerging trend in real-time signal processing
systems is to accelerate computationally intensive
algorithmic components by mapping them to custom or
reconfigurable hardware platforms, such as application-
specific integrated circuits (ASICs) and field-
programmable gate arrays (FPGAs). Most of these
algorithms are initially developed in software using
floating-point representation and later migrated to
hardware using finite precision (e.g., fixed-point
representation) for achieving improved computational
performance and reduced hardware cost. These
implementations are often parameterized, so that a wide
range of finite precision representations can be supported
[1] by choosing an appropriate wordlength for each
internal variable. As a consequence, the accuracy and
hardware resource requirements of such a system are
functions of the wordlengths used to represent the internal
variables. Determining an optimal wordlength
configuration has been shown to be NP-hard [2] and can
take up to 50% of the design time for complex systems
[3]. Moreover, a single optimal solution may not exist,
especially in the presence of multiple conflicting
objectives. In addition, a new configuration generally
needs to be derived when the design constraints are
altered.
The problem of finding optimal wordlength
configurations can be formulated as a multiobjective
optimization, where different objectives — for example,
accuracy and area — generally conflict with one another.
Although this approach increases the complexity of the
search, it can find a set of Pareto-optimized configurations
representing strategically-chosen tradeoffs among the
various objectives. This allows a designer to choose an
efficient configuration that satisfies given design
constraints and provides ease and flexibility in modifying
the design configuration as the constraints change.
An optimum wordlength configuration can be
identified by analytically solving the quantization error
equation as described in [4-8]. This analytical
representation, however, can be difficult to obtain for
complex systems. Techniques based on local search or
gradient-based search [9] have also been employed, but
these methods are limited to finding a single feasible
solution as opposed to an optimized tradeoff curve. An
exhaustive search of the entire design space is guaranteed
16th International Symposium on Field-Programmable Custom Computing Machines
978-0-7695-3307-0/08 $25.00 © 2008 IEEE
DOI 10.1109/FCCM.2008.50
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to find Pareto-optimal configurations. Execution time for
such exhaustive search, however, increases exponentially
with the number of design parameters, making it
unfeasible for most practical systems. Methods that
transform this problem into a linear programming problem
have also been reported [4], but these techniques are
limited to cases in which the objectives can be modeled as
linear functions of the design parameters. Other
approaches based on linear aggregation of objectives may
not find proper Pareto-optimal solutions when the search
space is nonconvex [10]. Techniques based on
evolutionary methods have been shown to be effective in
searching large search spaces in an efficient manner [11,
12]. Furthermore, these techniques are inherently capable
of performing multipoint searches. As a result, techniques
based on evolutionary algorithms (EA) have been
employed in the context of multiobjective optimization
(SPEA2 [13], NSGA-II [14]).
This article presents a novel multiobjective
optimization strategy developed in the context of FPGA-
based implementation of medical image registration. The
tradeoff between FPGA resources (area and memory) and
implementation accuracy is explored, and Pareto-
optimized solutions are identified. This analysis is
performed by treating the wordlengths of the internal
variables as design variables. We also compare several
search methods for finding Pareto-optimized solutions and
demonstrate the applicability of search based on
evolutionary techniques for efficiently identifying superior
multiobjective tradeoff curves. This optimization strategy
can easily be adapted to a wide range of signal and image
processing applications.
This paper is organized as follows. Section 2 provides
background on image registration and outlines an
architecture for its FPGA-based implementation. The
formulation of the multiobjective optimization and various
search methods to find Pareto-optimized solutions are
described in Section 3. Section 4 presents experimental
results and compares various search methods. In Section 5,
related work for optimum wordlength search and
multiobjective optimization is presented. Section 6
concludes the paper.
2. Image registration
Medical image registration is the process of aligning
two images that represent the same anatomy at different
times, from different viewing angles, or using different
imaging modalities. This method attempts to find the
transformation (
ˆ
T
) that optimally aligns a reference image
(RI) with coordinates x, y, and z and a floating image (FI)
under an image similarity measure (
F ):
ˆ
arg max ( ( , , ), ( ( , , ))).
T
TRIxyzFITxyz= F (1)
Many image similarity measures, such as the sum of
squared differences and cross correlation, have been used,
but mutual information (MI) has recently emerged as the
preferred similarity measure. MI-based image registration
has been shown to be robust and effective in
multimodality image registration [15]. However, this form
of registration typically requires thousands of iterations
(MI evaluations), depending on image complexity and the
degree of initial misalignment between images. Castro-
Pareja et al. [16] have shown that, calculation of MI for
different candidate transformations is a factor limiting the
performance of MI-based image registration. We have,
therefore, developed an FPGA-based architecture for
accelerated calculation of MI [17], which is capable of
computing MI 40-times faster as compared to software
implementation.
2.1. FPGA-based implementation of mutual
information calculation
During the execution of image registration using this
architecture, the optimization process is executed from a
host workstation. The host provides a candidate
transformation, while the FPGA-based implementation
applies it to the images and performs the corresponding
MI computation. The computed MI value is then further
used by the host to update the candidate transformation
and eventually find the optimal alignment between the RI
and FI. Figure 1 shows the top-level block diagram of the
aforementioned architecture. The important modules in
this design are described in the following subsections.
2.1.1. Voxel counter. Calculation of MI requires
processing each voxel in the RI. In addition, because the
implemented algorithm processes the images on a
subvolume basis, RI voxels within a 3D neighborhood
corresponding to an individual subvolume must be
processed sequentially. The host programs the FPGA-
based MI calculator with subvolume start and end
addresses, and the voxel counter computes the address
corresponding to each voxel within that subvolume in
z
y
x order.
2.1.2. Coordinate transformation. The initial step in MI
calculation involves applying a candidate transformation
(T), to each voxel coordinate (
r
v
) in the RI to find the
corresponding voxel coordinates in the FI (
f
v
). This is
mathematically expressed as:
.
f
r
vTv
=
(2)
The deformation model employed is a six-parameter
rigid transformation model and is represented using a
4 × 4 matrix. The host calculates this matrix based on the
current candidate transformation provided by the
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optimization routine and sends it to the MI calculator. A
fixed-point representation is used to store the individual
elements of this matrix. The coordinate transformation is
accomplished by a simple matrix multiplication.
2.1.3 Partial volume interpolation. The coordinates
mapped in the FI space (
f
v
) do not normally coincide
with a grid point (integer location), thus requiring
interpolation. Nearest neighbor and trilinear interpolation
schemes have been used most often for this purpose;
however, partial volume (PV) interpolation, introduced by
Maes et al. [15] has been shown to provide smooth
changes in the histogram values with small changes in
transformation. The reported architecture consequently
implements PV interpolation as the choice of interpolation
scheme.
f
v
in general, will have both fractional and
integer components and will land within an FI
neighborhood of size 2 × 2 × 2. The interpolation weights
required for the PV interpolation are calculated using the
fractional components of
f
v
. Fixed-point arithmetic is
used to compute these interpolation weights. The
corresponding floating voxel intensities are fetched by the
image controller in parallel using the integer components
of
f
v
. The image controller also fetches the voxel
intensity corresponding to
r
v
. The MH then must be
updated for each pair of reference and floating voxel
intensities (eight in all), using the corresponding weights
computed by the PV interpolator.
2.1.4. Image memory access. The typical size of 3D
medical images prevents the use of high-speed memory
internal to the FPGA for their storage. Between the two
images, the RI has more relaxed access requirements,
because it is accessed in a sequential manner (in
z
y
x
order). This kind of access benefits from burst accesses
and memory caching techniques, allowing the use of
modern dynamic random access memories (DRAMs) for
image storage. For the architecture presented, both the RI
and FI are stored in separate logical partitions of the same
DRAM module. Because the access to the RI is sequential
and predictable, the architecture uses internal memory to
cache a block of RI voxels. Thus, during the processing of
that block of RI voxels, the image controller has parallel
access to both RI and FI voxels. The RI voxels are fetched
from the internal FPGA memory, whereas the FI voxels
are fetched directly from the external memory.
The FI, however, must be accessed randomly
(depending on the current transformation
T) and eight FI
voxels (a 2 × 2 × 2 neighborhood) must be fetched for
every RI image voxel to be processed. To meet this
memory access requirement, the reported architecture
employs a memory addressing scheme similar to the cubic
addressing technique reported in the context of volume
rendering [18]. A salient feature of this technique is that it
allows simultaneous access to the entire 2 × 2 × 2 voxel
neighborhood. The reported architecture implements this
technique by storing four copies of the FI and taking
advantage of the burst mode accesses native to modern
DRAMs. The image voxels are arranged sequentially such
that, performing a size two burst fetches two adjacent
2 × 2 neighborhood planes, thus making the entire
neighborhood available simultaneously. The image
intensities of this neighborhood are then further used for
updating the MH.
2.1.5. Updating the mutual histogram. For a given RI
voxel (
RV), there are eight intensity pairs (RV, FV
0
: FV
7
)
and corresponding interpolation weights. Because the MH
must be updated (read–modify–write) at these eight
locations, this amounts to 16 accesses to MH memory for
each RI voxel. This high memory access requirement is
handled by using the high-speed, dual-ported memories
internal to the FPGA to store the MH. The operation of
updating the MH is pipelined and, hence, read-after-write
(RAW) hazards can arise if consecutive transactions
attempt to update identical locations within the MH. The
reported design addresses this issue by introducing pre-
accumulate buffers, which aggregate the weights from all
conflicting transactions. Thus, all the transactions leading
to a RAW hazard are converted into a single update to the
MH, thereby eliminating any RAW hazards.
While the MH is being computed, the individual
histogram accumulator unit computes the histograms for
the RI and FI. These individual histograms are also stored
using internal, dual-ported memories. The valid voxel
Figure 1: Top-level block diagram of FPGA-based
architecture for MI calculation
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counter module keeps track of the number of valid voxels
accumulated in the MH and calculates its reciprocal value.
The resulting value is then used by the entropy calculation
unit for calculating the individual and joint probabilities.
2.1.6. Entropy Calculation. The final step in MI
calculation is to compute joint and individual entropies
using the joint and individual probabilities, respectively.
To calculate entropy, it is necessary to evaluate the
function
f(p) = p·ln(p) for all the probabilities. As each
probability
p takes values between [0,1], the
corresponding range for the function
f(p) is [e
1
,0]. Thus,
f(p) has a finite dynamic range and is defined for all values
of
p. Several methods for calculating logarithmic functions
in hardware have been reported [19], but of particular
interest is the multiple lookup table (LUT)–based
approach introduced by Castro-Pareja et al. [20]. This
approach minimizes the error in representing
f(p) for a
given number and size of LUTs and, hence, is accurate
and efficient. Following this approach, the reported design
implements
f(p) using multiple LUT–based piecewise
polynomial approximation.
3. Multiobjective optimization
The aforementioned architecture is designed to
accelerate the calculation of MI for performing medical
image registration. We have demonstrated this architecture
to be capable of offering execution performance superior
to that of a software implementation [17]. The accuracy of
MI calculation (and by extension, that of image
registration) offered by this implementation, however, is a
function of wordlengths chosen for the internal variables
of the design. Similarly, these wordlengths also control the
hardware implementation cost of the design. For medical
applications, the ability of an implementation to achieve
the desired level of accuracy is of paramount importance.
It is, therefore, necessary to understand the tradeoff
between accuracy and hardware implementation cost for
this design and to identify wordlength configurations that
provide effective tradeoffs between these conflicting
criteria. This multiobjective optimization will allow a
designer to systematically maximize accuracy for a given
hardware cost limitation (imposed by a target device, for
example) or minimize hardware resources to meet the
accuracy requirements of a medical application.
The following section provides a formal definition of
this problem and the subsequent section describes a
framework for multiobjective optimization of FPGA-
based medical image registration.
3.1. Problem statement
Consider a system
Q that is parameterized by N
parameters
n
i
(i = 1, 2, …, N), where each parameter can
take a single value from a corresponding set of valid
values (
v
i
). Let the design configuration space
corresponding to this system be
S, which is defined by a
set consisting of all
N-tuples generated by the Cartesian
product of the sets
v
i,
i :
123
.
N
Svvv v
=
×××× (3)
The size of this design configuration space is then equal
to the cardinality of the set
S or, in other words, the
product of cardinalities of the sets
v
i
:
123
.
N
Svvv v=×××× (4)
For most systems, not all configurations that belong to
S
may be valid or practical. We therefore define a subset
(
S), such that it contains all the feasible system
configurations. Now consider
m objective functions (f
1
, f
2
,
…,
f
m
) defined for system Q, such that each function
associates a real value for every feasible configuration
c∈ℑ.
The problem of multiobjective optimization is then to
find a set of solutions that simultaneously optimize the
m
objective functions according to an appropriate criterion.
The most commonly adopted notion of optimality in
multiobjective optimization is that of Pareto optimality.
According to this notion, a solution
c
is Pareto optimal if
there does not exist another solution
c∈ℑ such that
f
i
(c) f
i
(c
), for all i, and f
j
(c) < f
j
(c
), for at least one j.
Given a multiobjective optimization problem and a
heuristic technique for this problem that attempts to derive
Pareto-optimal or near-Pareto-optimal solutions, we refer
to solutions derived by the heuristic as “Pareto-optimized”
solutions.
3.2. Multiobjective optimization framework
Figure 2 illustrates the framework that we have
developed for multiobjective optimization of the
aforementioned architecture. There are two basic
components of this framework. The first component is the
search algorithm that explores the design space and
generates feasible candidate solutions; and the second
component is the objective function evaluation module
that evaluates candidate solutions. The solutions and
associated objective values are fed back to the search
algorithm, so that they can be used to refine the search.
These two components are loosely coupled so that
different search algorithms can be easily incorporated into
the framework. Moreover, the objective function
evaluation module is parallelized using a message passing
interface (MPI) on a 32-processor cluster. With this
parallel implementation, multiple solutions can be
evaluated in parallel, thereby increasing search
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performance. These components are described in detail in
the following sections.
3.2.1. Design parameters.
As described in the earlier
section, the architecture performs MI calculation using a
fixed-point datapath. As a result, the accuracy of MI
calculation depends on the precision (wordlength) offered
by this datapath. The design parameters in this datapath
define the design space and are identified and listed along
with the corresponding design module (see Figure 1) in
Table 1.
A fixed-point representation consists of an integer part
and a fractional part. The number of bits assigned to these
two parts are called the integer wordlength (IWL) and
fractional wordlength (FWL), respectively. The collective
number of bits allocated to these parts control the range
and precision of the fixed-point representation. For this
architecture, the IWL required for each design parameter
can be deduced from the range information specific to the
image registration application. For example, in order to
support translations in the range of [–64, 63] voxels, 7 bits
of IWL (with 1 bit assigned as a sign bit) are required for
the translation parameter. We used similar range
information to choose the IWL for all the parameters, and
these values are reported in Table 1. The precision
required for each parameter, which is determined by its
FWL, is not known a priori. We, therefore, determine this
by performing multiobjective optimization using the FWL
of each parameter as a design variable. In our experiments,
we used the design range of [1, 32] bits for FWLs of all
the parameters. The optimization framework can support
different wordlength ranges for different parameters,
which can be used to account for additional design
constraints, such as, for example, certain kinds of
constraints imposed by third-party intellectual property.
The entropy calculation module is implemented using a
multiple LUT–based approach and also employs fixed-
point arithmetic. However, this module has already been
optimized for accuracy and hardware resources, as
described in [20]. The optimization strategy employed in
[20] uses an analytical approach that is specific to entropy
calculation and is distinct from the strategy presented in
this work. This module, therefore, does not participate in
the multiobjective optimization framework of this paper,
and we simply use the optimized configuration identified
earlier. This further demonstrates the flexibility of our
optimization framework to accommodate arbitrary
designer- or externally-optimized modules.
3.2.2. Search algorithms.
An exhaustive search that
explores the entire design space is guaranteed to find all
Pareto-optimal solutions. However, this search can lead to
unreasonable execution time, especially when the
objective function evaluation is computationally intensive.
For example, with four design variables, each taking one
of 32 possible values, the design space consists of 32
4
solutions. If the objective function evaluation takes 1
minute per trial (which is quite realistic for multiple MI
calculation using large images), the exhaustive search will
take 2 years. Consequently, we considered other search
methods as described below.
The first method is
partial search, which explores only
a portion of the entire design space. For every design
variable, the number of possible values it can take is
reduced by half by choosing every alternate value. A
complete search is then performed in this reduced search
space. This method, although not exhaustive, can
effectively sample the breadth of the design space. The
second method is
random search, which involves
randomly generating a fixed number of feasible solutions.
For both of these methods, Pareto-optimized solutions are
identified from the set of solutions explored.
Figure 2: Framework for multiobjective optimization of
FPGA-based image registration
Table 1: Design variables for FPGA-based architecture. Integer wordlengths are determined based on application-specific
range information, and fractional wordlengths are used as parameters in the multiobjective optimization framework
Architectural
Module
Design
Variable
Integer wordlength
(IWL ) (bits)
Fractional wordlength (FWL)
range (bits)
Translation vecto
r
7 [1,32] Voxel coordinate
transformation
Rotation matrix 4 [1,32]
Partial volume interpolation Floating image address 27 [1,32]
Mutual histogram accumulation Mutual histogram bin 25 [1,32]
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Journal ArticleDOI
TL;DR: This article presents a widely parallel and deeply pipelined hardware CG implementation, targeted at modern FPGA architectures, particularly suited for accelerating multiple small-to-medium-sized dense systems of linear equations and can be used as a stand-alone solver or as building block to solve higher-order systems.
Abstract: Recent developments in the capacity of modern Field Programmable Gate Arrays (FPGAs) have significantly expanded their applications. One such field is the acceleration of scientific computation and one type of calculation that is commonplace in scientific computation is the solution of systems of linear equations. A method that has proven in software to be very efficient and robust for finding such solutions is the Conjugate Gradient (CG) algorithm. In this article we present a widely parallel and deeply pipelined hardware CG implementation, targeted at modern FPGA architectures. This implementation is particularly suited for accelerating multiple small-to-medium-sized dense systems of linear equations and can be used as a stand-alone solver or as building block to solve higher-order systems. In this article it is shown that through parallelization it is possible to convert the computation time per iteration for an order n matrix from Θ(n2) clock cycles on a microprocessor to Θ(n) on a FPGA. Through deep pipelining it is also possible to solve several problems in parallel and maximize both performance and efficiency. I/O requirements are shown to be scalable and convergent to a constant value with the increase of matrix order. Post place-and-route results on a readily available VirtexII-6000 demonstrate sustained performance of 5 GFlops, and results on a Virtex5-330 indicate sustained performance of 35 GFlops. A comparison with an optimized software implementation running on a high-end CPU demonstrate that this FPGA implementation represents a significant speedup of at least an order of magnitude.

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323, 328, 1042, 720, 1102, 737, 397, 398, 793, 1063, 1120, 415, 178, 851, 426, 889] brest, [445, 242, 263] cervical, [719, 757] chemotherapy, [635] chemotherapy control, [1110] colon, [331, 799, 830] Subject index 45 decision support, [749] detection, [926] drug design, [51, 75] genetics, [755] leucemia, [428] leukemia, [110] liver, [803, 425, 433] lung, [278, 408, 1119] mammograpgy, [262] mammography, [533, 206, 239, 243, 245, 247, 265] markers, [846] melanoma, [945, 960, 965, 588, 280, 283, 289, 627, 548, 549, 351, 747] nasopharyngeal, [1065, 835] oral, [166, 758, 1125] ovarian, [713, 908] prostate, [325, 732, 784, 414] radiotherapy, [572, 574, 602, 1044, 1099, 1049, 1050] sarcoma, [569] screening, [784] skin tumor, [525] spectral imaging, [426] survival, [1063] treatment, [954] cancer classification, [756] cancer radiotherapy, [971] CANFIS, [550] cardiology, [520, 292] acute coronary syndromes, [675] arrhythmia, [970] atherosclerotic plaque, [660, 348] beats, [1052] diagnosis, [573] Doppler, [1053] ECG, [671, 824] echo cardiography, [259] elastography, [348] heartbeat, [1107] heartbeat recognition, [760] hospital stay, [859] imaging, [496, 305, 362] infarction, [1008] risk model, [1057] stents, [754] CAT, [677] cDNA, [213] cellular automata, [201] cephalogram, [540] chemical shift lipid-water, [297] chemistry analytical, [973, 1024, 804, 863] combinatorial, [139] drug design, [120, 121, 128, 131, 133, 134, 138, 99] macromolecule, [141] medical, [438, 409] medicinal, [132] organic, [127, 634] physical, [117, 119] structural, [942, 955, 130, 137, 140, 18, 19, 22, 25, 30, 772, 55, 64, 65, 71, 76, 78, 79, 84, 847, 852, 101, 103, 109] chemometrics, [816, 92] drug design, [71] human serum, [905] QSAR, [707] chemometry infrared spectroscopy, [596] wavelength selection, [642] chemotherapy, [527] CHN, [128] chromatography, [1024, 92] gas-, [767] classification, [563, 918, 457, 952, 481, 505, 541, 575, 234, 578, 595, 598, 622, 1037, 1053] classification Bacillus, [725] biomedical information, [420] biopsy, [429] breast tumors, [415] cancer, [210, 331, 755, 856] EEG, [146, 801, 898, 899] feature selection, [887] fuzzy, [292] heartbeat, [1107] heartbeats, [1052] medical diagnosis, [339] medical images, [362] noun, [796] RNA, [171] rules, [944, 961] soft tissue, [1111] swallow, [735] tachycardia, [906] tissue, [940] tumors, [456] classifier fuzzy, [951, 1070] classifier systems, [553, 562, 929, 576] emergency, [1166] classifiers, [560, 962, 1161] cancer, [908] feature selection, [478] features, [1145] fuzzy, [1108] heartbeat, [760] lymph diseases, [1074] mammography, [733] medical, [383] spectral, [1145] SVM, [876] clinic scheduling, [892] cluster analysis evolutionary, [697] clustering, [588, 262, 265, 623, 652, 669, 336] clinical data, [943] DNA, [209] feature selection, [623] fuzzy, [1083] gene expression, [819] 46 Genetic algorithms in medicine initialization, [365] k-means, [888] protein interaction, [886] toxicity, [586] clusters rare disease, [762] co-evolution cooperative, [598] cochlea implant, [375] coding real, [584, 896] coevolution, [629] fuzzy, [587] cognition testing, [287] visual, [1163] color medical image visualisation, [312] colors visualization, [344] comparison classification methods, [1000] cost-sensitive classification, [921] GA worse, [1156] human, [688] image registration, [352] in classification, [1035] in CT reconstruction, [497] in diagnosis, [985, 1013] in docking, [142] in image registration, [349, 381, 384, 386, 388, 395] in image thresholding, [428] in machine learning, [918, 805] in medical data mining, [258] in melanoma prediction, [960] in protein folding, [129] in regression, [950] in tomography reconstruction, [340] in wavelength selection, [1059] logistic regression, [647] Maxent, [706] Nelder-Mead, [557, 1079] neural networks, [945, 1035, 1035] particle swarm, [381, 388] SA in image registration, [333] simple stochastic algorithm, [1156] simulated annealing, [226, 129, 1088, 340] stepwise linear regression, [968] vector quantisation, [913] Very Fast Simulated ReAnnealing, [557] compression selective, [508] computational geometry, [137] computer graphics color, [344] polygonal approximation, [1147] conotoxin Conus geographicus, [942] control, [1080, 610] blood pressure, [920] glucose, [809] motion, [339] prosthesis, [667] protheses, [554] wheelchair, [1109] controller fuzzy, [932] controllers fuzzy, [1104] prosthetic hand, [593] criminology, [1167] crossover real, [584] CT angiography, [382] brain, [341] cancer, [403] lung, [372, 399, 1061] micro-, [412] reconstruction, [497] ROI, [372] cytology axonal outgrowth, [1105] image processing, [1037] imaging, [210] data analysis medical, [236] data mining, [968, 238, 674, 420] medical, [236, 258, 392] microarrays, [208] databases, [566] data mining, [244] medical, [238, 244, 288] retrieval, [288] datamaining, [698] decision support medical, [527] decision support systems medical, [1038] decision trees, [921, 166] decisions diagnostics, [629] medical, [484] dentistry imaging, [511] periodontal, [862] depression EEG, [1068] dermatology chemical penetration, [659] dermatoscope, [351] erythema, [693] lesions, [401] skin lesions, [400] urticaria, [868] wound healing, [673] design by human, [890] implant, [640, 664] detistry periodontitis, [207] Subject index 47 diabetes diagnosis, [840] fuzzy reasoning, [1058] glucose control, [1104] glucose sensing, [650, 651] leg ulcers, [368, 195, 1048, 390] retinal images, [1035] retinopathy, [1035] retipathy, [547] sensoring, [649] diagnosis, [1090] breast cancer, [598, 328] cancer, [951, 1011, 1015] cardiac disease, [550] cardiology, [573] diabetes, [1035, 1035] failure, [578] fault, [253] mammography, [986] medical, [485, 486, 489, 240, 253, 261] melanoma, [965] myocardial heart disease, [990] variable selection, [644] diagnostics caries, [17] confidence measure, [1051] hypovolemia, [730] tuberculosis, [1103] dietary menu planning, [1146] differential evolution, [428] image registration, [192] regression, [380] digital logic, [593] discussion [602], [594, 606] DNA, [135, 136] analysis, [197] microarray, [741] motifs, [1150] sequence alignment, [1156, 727] transposable elements, [160] docking, [125, 126] drug design, [20, 117, 118, 119, 122, 123, 125, 126, 127, 130, 132, 133, 134, 135, 136, 137, 139, 140, 141, 18, 19, 21, 22, 23, 24, 25, 26, 28, 60, 106] drug design antibiotics, [56] cancer, [42] computational, [30, 75] de novo, [87] DNA breeding, [29] docking, [74] HIV-1, [49] in silico, [63] MMP-12 inhibitors, [31] pharmacokinetics, [57] QSAR, [124, 32, 33, 34, 36, 37, 38, 39, 40, 41, 43, 47, 48, 52, 54, 69, 81, 82, 90, 91, 94, 96, 98] renal anion transporter inhibitors, [89] screening, [61] SVM, [53] thrombin inhibitor, [35] virtual screening, [67] ECG, [956, 996] P wave, [538] echocardiography, [223, 224] ecology antrax, [681] distribution, [1097] GARP, [706, 710, 1101] hemorrhagic fever, [855] modeling, [628] niche modeling, [636, 681] species distribution, [674, 686, 1098, 699, 700, 711] species distriution, [702] economics heathcare, [643] edge detection, [498] EEE source modeling, [150] EEG, [930] classification, [144] epilepsy, [145, 146] electrical impedance tomography reconstruction, [1036] electromagnetics, [452, 461, 473, 976, 1157] antennas, [279] brain stimulation, [1160] Kirlian imaging, [234] microwaves, [314] MRI, [302, 313] tissue, [798] electromagnetism coils, [506] electromyogram, [493] elitism, [1138, 506] EMG, [563, 500] endocrinology neural, [662] engineering aerospace, [253] civil, [314] mechanical, [663, 1076] medical, [228, 314] nano-, [649] process, [728, 731, 110] radio, [461] entomology flea, [310] medical, [310] environment pollution, [888] epidemiology malaria, [949] vectors, [636] epilepsy prediction, [1034] ergonomy back, [962] erythema UV induced, [693] evolution, [153, 1020] incremental, [593] 48 Genetic algorithms in medicine interactive, [687] recombination, [161, 162] simulation, [167] evolution strategies, [564, 561, 1019, 912, 605] medicine, [1021, 568] tomography, [270] evolutionary programming, [558] evolutionary strategies 1+1, [191] evolvable hardware FPGA, [667] experimental design, [287] Taguchi, [663] expert systems, [952, 489, 982, 1000, 591, 253] fuzzy, [261] medical, [449, 257] feature extraction, [540, 575] microarray, [1148] feature selection, [944, 961, 542, 26, 1055, 171, 1115, 846, 877, 113] feature selection DNA microarray, [741] drug design, [27] oral cancer, [758] QSAR, [38] features extraction, [233, 255] FEM, [663, 677] Bezier surface, [640, 664] brain stem, [1078] elastography, [348] injury, [729] fermentation drug production, [731] Gibberella fujikuroi, [207] figure copying task, [339] filters Gabor, [411] matched, [1041] median, [454] morphological, [451, 293, 413, 422] optical, [280] stack, [454] texture, [477] wavelet, [1108, 1154] finite element mesh, [660] fish oil, [815] fitness aesthetics, [691] in tomography, [317] interactive, [645, 676, 691] fluorescence imaging ICG, [380] forensics dental images, [15] Fourier series, [224] FPGA image processing, [411] fractals IFS, [1138] image analysis, [1035] fuzzy logic reasoning, [963, 517, 984] fuzzy reasoning, [609] fuzzy reasoningmachine learning fuzzy, [1119] fuzzy rules, [185] fuzzy sets, [446] fuzzy systems, [449, 1006, 1015, 598, 210, 286, 629, 70] ARTMAP, [46] classification, [730] decision support, [1113] finite state machine, [1037] image analysis, [912] image segmentation, [419] neural network, [550] neural networks, [830] prediction, [793] FuzzyCoCo, [609, 629] GA interactive, [890] GADELO, [557, 1079] games golf, [826] gamma knife, [718] GAP, [129] GARP, [1097, 310, 681, 686] climate change, [711] DesktopGARP, [674] GIS, [668, 679, 684] influenca, [696] influenza, [699] malaria, [1098] medicinal plant, [751] monkeybox, [700] niche modeling, [636, 710] plague, [695] West Nile virus, [702] gastronomy diet, [637] Gaussian mixture model image segmentation, [382] gene regulatory network modeling, [817] genetic gene regulation, [761] human, [658] genetic algorithm classification, [548] genetic code, [188] genetic programming, [915, 444, 471, 238, 620, 164, 283, 289, 657, 673, 678, 339] genetic programming classification, [456] image processing, [282] in biochemistry, [207] interactive, [288] linear, [258] regression, [647] genetics, [153, 151, 152, 156, 154, 155, 183, 184, 158, 160, 166, 174, 181, 182] genetics bacterial, [185] breast cancer, [178] D. melanogaster, [161, 162] Subject index 49 DNA, [159] essential genes, [180] gene expression, [175] gene order, [177] gene regulation, [172] gene regulatory networks, [173] gene-gene interaction, [164] mapping, [186] phylogeny, [163] promoter prediction, [170] proteins, [157] proteome, [176] RNA, [171] salmon, [167] selection, [188, 168] sequence alignment, [187] SNP, [165, 179] virus, [169] GENIE, [638] genome microRNA precursors, [769] geometric modeling, [958] 3D, [488] GFA, [968] GIS GARP, [310] glucose, [973, 642] Gnets, [231] GP parallel, [362] grammars, [238] grippers design, [631] GRNN, [242, 263] hardware evolvable, [998] health monitoring, [228] hearing aid, [610] hematology chromatography, [767] glycans, [813] tacrolimus, [833] hemodynamics anastomosis, [808] brain, [776] hepatitis therapy, [744] hepatology fibrosis, [753] hip arthroplasty, [599] histology, [481] cancer, [518, 210] lung, [429] tissue classification, [940] HIV, [115] drug design, [45] therapy planning, [759] HIV-1, [46] human plasma triglycerides, [597] hybrid Bayesian network, [725] downhill simplex, [373] FEM, [660] fuzzy logic, [1025, 790] GP and logic programming, [238] gradient, [931] gradient based method, [446] local gradient, [308] local search, [117, 322, 56] maximum likelihood method, [294] neural network, [103] neural networks, [935, 493, 995, 1025, 54, 56, 875, 880] perceptron, [1128] QSAR, [90] simulated annealing, [130, 1093, 211, 626] SVM, [43, 44, 1111, 407, 415, 179] tabu-search, [300] image analysis, [308] image correction deformation, [332] image fusion medical, [359] image processing, [204, 226, 556, 200, 440, 468, 469, 476, 477, 480, 498, 533, 346, 422] image processing 3D, [227] automatic, [282] border detector, [915] classification, [516] compression, [508, 1026] CT, [543] edge detection, [475] enhancement, [218] feature extraction, [463, 1083] feature selection, [458, 408] filters, [293, 413] high-speed video, [1040] image registration, [225, 284, 335, 1064] magnetic resonance, [915] matching, [453] medical, [223, 224, 227, 229, 230, 231, 441, 443, 446, 447, 448, 455, 464, 470, 471, 507, 518, 234, 256, 1073] morphological, [439] motion estimation, [305] pattern recognition, [249] reconstruction, [466, 472, 487, 490, 543] registration, [501, 1088, 254, 277, 371, 379, 421, 423, 432, 435] restoration, [454] segmentation, [910, 437, 448, 471, 502, 505, 220, 523, 534, 544, 232, 588, 266, 212, 273, 275, 276, 278, 280, 624, 283, 289, 296, 638, 652, 324, 343, 1118, 417, 1073] shape, [216, 326] stereo, [692] symmetry, [368, 195, 1048, 390] texture, [233, 255, 425, 433] thresholding, [428] tomography, [1036] ultra sound, [274] wavelets, [458] image processing?, [460] 50 Genetic algorithms in medicine image registration, [446, 511, 539, 1022, 191, 15, 311, 322, 328, 342, 355, 358, 370, 379, 381, 386, 388, 395, 403, 902] image registration 3D, [227, 439, 501, 522, 252, 271, 300, 301, 304, 321, 356] CT and ultrasound, [352] dental, [16] fiducial configuration, [1100] landmark, [319] local, [319] MRI, [528] multimodal, [333] multiresolution, [423] mutual information, [271, 192, 299, 330, 349, 373, 393, 405, 410] non rigid, [1047] non-rigid, [303] optic nerve, [384] PSO, [1064] retina, [359] retinal angiograms, [364] voxel, [421, 432] image segmentation, [14, 669] Gaussian mixture model, [377] thresholding, [428] imaging 3D, [488, 305] brain, [442, 306] color design, [737] CT, [303, 1111] electrical impedance, [459] eye, [1041] fusion, [737] hyperspectral, [207, 196] Kirlian, [234] magnetic resonance, [329, 1043] medical, [440, 442, 453, 459, 460, 464, 468, 469, 473, 474, 479, 480, 483, 488, 491, 494, 495, 496, 498, 507, 509, 511, 512, 514, 516, 517, 520, 525, 532, 543, 546, 547, 237, 249, 256, 259, 273, 280, 282, 283, 289, 292, 293, 296, 1041, 426] MRI, [303] multispectral, [526, 335, 351, 799] NMR, [509, 524, 539, 237] ultrasonic, [496, 517, 251] ultrasound, [1030, 1031, 303, 425, 433, 908] imaging skin, [283, 289] immune system simulator, [1144] immunology, [967] simulator, [1144] implant FEM, [641, 672] implants, [499] cochlear, [639, 645, 676] design, [640] prostate, [992] titanium, [664] implementation bacteria, [136] Fortran 77, [135] FPGA, [667, 692] LabView, [1080] MIMD, [117] IMRT, [1106] indocyanine green angiography, [311] tissue perfusion, [380] infection influenza, [696] malaria, [1098, 706] plague, [695] infections classification, [712] Helicobacter pylori, [724] inflammation intracellular signaling, [722] influenza avian, [696] injury pulmonary, [729] insects mosquitoes, [674] integer programming, [992] interactive GA, [375, 884] inverse problems, [229, 671] CT, [1061] ECG, [873] EEG, [143] electrocardiography, [1132] electromagnetics, [314] medical, [1086] MEG, [1086] neuromagnetism, [1165] optical, [203] radiotherapy, [581] scattering, [774] thermal, [1082] tomography, [353] knee arthroplasty, [592] knowledge based systems, [257] Kohonen nets, [552] laparoscopy artery cross-clamping, [879] laryngology swallow, [735] layout ambulance locations, [708] learning evolution, [189] learning classifier systems, [166] ligands, [142] LINKERS, [1142] liver, [436] angiography, [382] diagnosis, [1126] texture, [212] transplantation, [833] logic programming, [238] LVQ, [913] machine learning, [562, 449, 935, 480, 959, 489, 1084, 981, 982, 548, 316, 698] machine learning classification, [1035] Subject index 51 clustering, [697] Gaussian mixture model, [14] genetic programming, [653] image features, [408] kernel-based, [669] medicine, [553] machine vision registration, [969] macromolecules, [122, 139, 141] DNA, [160, 214] docking, [21] peptides, [135] RNA, [955] macrosomia, [812] magnetoencephalography, [229] malari vectors, [674] malaria vector invasion risk, [686] vectors, [1097] mammography, [445, 457, 940, 476, 988, 233, 255, 629, 292] asymmetry, [397] diagnosis, [1012] microcalcification, [507, 249] mamography, [535] maps, [588] mass spectroscopy clinical, [834] matching, [274] mechanics fluid dynamics, [194] fluidics, [632] medical imaging, [225, 437, 441, 445, 451, 454, 455, 457, 459, 463, 476, 477, 478, 481, 482, 502, 505, 518, 523, 526, 531, 533, 534, 537, 540, 544, 545, 232, 233, 235, 239, 243, 245, 247, 191, 255, 1030, 260, 262, 265, 277, 298, 348, 352, 370, 381, 384, 386, 388, 395, 429] medical imaging 3D, [1022] angiography, [286] arteries, [1031] blood vessels, [447, 467, 475] brain, [439, 465, 501, 528, 268, 275, 299, 301, 307, 330, 332, 333, 343, 357, 419, 430, 435] breast cancer, [422] cancer, [203, 535, 242, 263, 193, 323] cardiology, [503, 508, 362] chest, [485] coloring, [328] compression, [1026] CT, [466, 487, 497, 267, 268, 326, 341, 372, 377, 378, 399, 1061, 406, 412, 423, 430] CT scans, [278] dental, [14, 15, 16, 17] dermatology, [391] diabetes, [530] drug discovery, [335] ECG, [541] EMRI, [367] endoscopy, [331] fluorescence, [380] fMR, [389] fMRI, [287, 404] fusion, [328] heart, [305] histology, [1037, 355] image quality, [402] image registration, [522, 252, 268, 271, 272, 284, 192, 299, 303, 304, 318, 319, 321, 322, 345, 349, 360, 373, 393, 405, 410, 421, 432] image segmentation, [306] impedance tomography, [510] ITK, [191] leucemia, [428] liver, [425, 433] lung, [403, 408, 416, 417] MALDI, [387] mammography, [542, 1042, 397, 398] melanoma, [548, 549] microwave, [246] monitoring, [294] MR, [286, 379, 435] MRI, [529, 266, 271, 279, 291, 295, 354, 297, 302, 306, 313, 329, 332, 337, 1043, 366, 371, 407, 413, 414, 418] multi-modal, [522] neurology, [356] neutron, [472] NMR, [452, 506, 524, 539, 343] online, [411] optical, [351, 368, 195, 1048, 390] optical tomography, [325, 1067] PET, [327, 357] pulmonary embolisms, [394] radiographs, [462] registration, [254] retina, [1035, 290, 294, 308, 311, 324, 336, 342, 358, 359, 364] segmentation, [251, 281, 315, 1046, 376, 382] skin, [401] skin lesions, [400] sonar, [458] SPECT, [268, 270] surgery, [356] thermography, [385] thresholding, [434] tomography, [436, 198, 490, 241, 248, 285, 300, 314, 317, 334, 334, 338, 340, 350, 353, 363, 365, 369, 374, 396] tumors, [456] ultrasonic, [470] ultrasound, [513, 274, 276, 415, 427] videofluoroscopy, [1047] visual, [347] visualisation, [312] visualization, [344] X-ray, [504] x-ray, [309] X-ray, [1042] medical imaging?, [461] medical signal processing ECG, [431] EEG, [320] genetic programming, [149] 52 Genetic algorithms in medicine medicien Alzheimer’s disease, [177] medicin oncology, [1050] medicinal plant distribution, [751] medicine, [564, 558, 1019, 555, 557, 565, 1004, 583, 589, 608] medicine , [791, 806] accident resource allocation, [869] administration, [643, 1112, 1129, 892] alcoholics, [930] anaesthesia, [932, 590] anaesthesiology, [975] anatomy, [958, 624] andrology, [933] anesthesia, [578] anthrax, [668, 681] antibiotics, [56] arteries, [1054] arteriology, [656] Bacillus anthracis, [711] bacteriology, [863] behavior dynamics, [857] bibliography, [1018] biomarkers, [794, 812] blood, [642, 768, 1059] blood circulation, [808] brachyotherapy, [993] brachytherapy, [612, 614, 1002] brain interface, [736] brains, [446, 448] breast, [841] cancer, [445, 464, 940, 945, 947, 125, 950, 951, 954, 957, 960, 964, 965, 968, 979, 981, 518, 986, 988, 992, 525, 527, 1011, 1012, 1015, 569, 574, 205, 206, 1028, 587, 588, 598, 603, 1095, 615, 280, 627, 629, 634, 648, 548, 549, 1099, 704, 713, 719, 720, 1102, 747, 749, 1110, 755, 756, 757, 758, 51, 763, 397, 398, 784, 793, 803, 1063, 813, 1119, 1120, 1065, 830, 414, 415, 835, 1125, 846, 178, 851, 856, 425, 889, 433, 908] cardiology, [607, 223, 224, 231, 915, 920, 927, 931, 956, 217, 963, 1139, 503, 970, 517, 983, 984, 990, 532, 1008, 1030, 1033, 618, 657, 660, 671, 550, 675, 703, 709, 1052, 1053, 1107, 754, 1057, 760, 1113, 820, 824, 829, 859, 873, 1132, 906] cellular, [854] chemotherapy, [24] Chinese, [891] classification, [560] clinical classification, [1075] clinical trials, [559] consultation system, [914] critical care, [867] Crohn’s disease, [903] CT, [326] cynegology, [1117] cytology, [638, 1105] data processing, [916] decision support, [1010, 635, 1130] decision tree, [972] dengue, [636] dentisry, [1025] dentistry, [953, 828] dermatology, [1039, 659, 673, 693, 774, 401, 868] diabetes, [973, 649, 650, 651, 1104, 1058, 825, 840, 1070] diagnosis, [567, 921, 952, 959, 963, 1084, 219, 517, 982, 984, 985, 991, 1000, 531, 1006, 1013, 545, 573, 205, 206, 582, 595, 620, 622, 1035, 629, 647, 357, 1126] diagnostics, [246, 1094, 609, 680, 1051, 383, 1103, 730, 770, 1074] dianostics, [449] diet planning, [637] DNA, [741] drug design, [121, 122, 127, 128, 129, 130, 131, 140, 142, 27, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48, 49, 50, 52, 53, 54, 55, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 97, 100, 101, 102, 103, 104, 105, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116] drug development, [848] drug production, [731] drug testing, [816, 870, 897] ECG, [521] editorial, [689] EEG, [913, 1138, 736, 147, 887, 898, 899] electromyography, [562] EMG, [563, 935] endoscopy, [269] environmental, [613, 852, 888] epidemiology, [929, 576, 628, 636, 1097, 668, 674, 679, 684, 686, 738, 855, 885] ergonomy, [962] estimation, [723] fungi, [787] gait, [1089] gastroenterology, [644] gastrology, [486, 1090] genetic, [761, 842] genetic maps, [658] genetics, [580, 164, 727, 734, 172, 777, 781, 1116, 786, 788, 789, 792, 807, 810, 811, 173, 814, 817, 819, 175, 1066, 176, 839, 1127, 864, 876, 896] genome, [601, 769] geographics, [762] geriatry, [595] gerontology, [577] glaucoma, [616] glomerular filtration, [893] hearing, [645, 676, 687, 845, 872] hearing aid, [600] hematology, [597, 767, 1060, 813, 76] hemodynamics, [632, 194] hemorrhagic blood loss, [966] hepatitis, [744] hepatology, [995, 753] histology, [926, 575, 881] HIV, [923, 1009, 707, 45, 759, 886] HIV-1, [937] hospital mortality, [1001] human genetics, [918] Subject index 53 imaging, [227, 230, 910, 200, 442, 494, 370, 737, 1111] immunology, [728] implantable lung, [630, 646, 670] infection, [1098, 695, 696, 699, 700, 702, 706, 711] infections, [710, 712, 724, 1121] inflammation, [722] infrastructure, [1124] injury, [729] instrumentation, [561] K, [942] laparoscopic intruments, [617] laryngology, [735] learning, [948] liver, [833, 1071] lung, [416, 429] malaria, [949, 679, 684, 686] malaria medicine, [877] mammography, [925, 455, 460, 478, 492, 507, 985, 1013, 249, 604] management, [708] medicinal plant, [751] MEG, [229] metabolism, [716, 765, 797] metabolomics, [725] microbes, [837, 847, 1072] mobile service, [682] monitoring, [743] MR-imaging, [912] mutations, [658] neurology, [909, 935, 936, 944, 149, 961, 505, 976, 977, 980, 991, 150, 570, 143, 591, 1029, 605, 275, 1034, 286, 287, 639, 662, 307, 320, 685, 687, 688, 339, 705, 721, 1056, 389, 750, 144, 145, 779, 782, 404, 146, 407, 800, 801, 805, 822, 838, 418, 843, 1068, 866, 884, 148, 895, 901, 904, 1078, 1017] neurology?, [1062] neurosurgery, [1100] nuclear, [999] nutrition, [795] obstetrics, [236] odantology, [537] odontology, [862] oncology, [1014, 1092, 1093, 621, 626, 1096, 633, 166, 665, 1044, 694, 1045, 701, 1106, 773, 799, 426] ophthalmology, [969, 1088, 547, 1029, 1035, 290, 294, 652, 308, 669, 324, 1041, 336, 342, 780] oral, [511] orthopaedics, [804, 832, 834] orthopaedy, [663] orthopediatry, [688] orthopedics, [766, 778, 849, 894, 1076] orthopedy, [989, 1032, 641, 672] osteoporosis, [989, 853] oto-laryngologia, [726] paraplegia, [1007] pattern recognition, [623] peptides, [732] pharmacokinetics, [678] pharmacology, [586] pharmacy, [619] physiology, [939, 202, 946, 715, 746, 1108, 776, 783, 1115, 790, 406, 798, 809, 827, 890, 900] planning, [775] plastic surgery, [683, 691] pre-eclampsia, [653] prediction, [928] pregnancy, [752] prions, [116] prostate, [987, 237, 585] prostehesis, [667] prosthese, [1136, 998] prosthetic hand, [593] prosthetics, [274] proteins, [764, 844] proteome, [1122] protheses, [554] psychiatry, [978] psychitry, [571] psychology, [943, 997, 880, 882] radiation therapy, [199, 917, 1133] radio therapy, [572] radiology, [453, 941, 698, 717, 718, 733, 823, 1123, 865] radiotherapy, [612, 614, 911, 919, 1134, 934, 1135, 938, 941, 484, 971, 992, 1140, 1005, 581, 584, 1091, 585, 594, 602, 606, 654, 1049] report on activities, [590] review, [924] scoliosis, [871] sensing, [610] sensoring, [1081] sepsis, [867] serum, [905] signal processing, [996, 1003, 687] sleep apnea, [739] sleeping, [552] smoking cessation, [1079] sport, [745, 826] sports, [831] statistics, [785] stem cells, [740, 821] surgery, [920, 974, 578, 592, 599, 269, 611, 625, 631, 640, 655, 661, 664, 666, 677, 690, 697, 802, 878, 879, 902] TCM, [874] thermotherapy, [1082] tomography, [556] toxicology, [994, 714, 771, 772, 875] traffic injury, [883] triage, [1131] urology, [933, 952, 1084, 982, 1000, 257] vaccination, [1114] vaccines, [818, 850, 861] vectors, [1101] virology, [967, 742, 836, 860, 907] vision, [551] vision impairment, [692] vitamins, [815] vocal fold, [1040] voice, [748, 796] walking, [1077] would healing, [673] 54 Genetic algorithms in medicine yellow fever, [955] medine cardiology, [211] oncology, [210] melanoma, [957] metabolic profiling, [752] metabolism tracing, [797] metabolomics spectroscopy, [725] micro-arrays, [648] microarrays, [761] classification, [842] image processing, [213] microbes tuberculosis, [786] microbiology, [136] microscopy endoscopy, [331] modeling, [871] biochemistry, [1159] hemodynamics, [632] membrane potential, [662] polyominos, [683] MOGA, [630] molecular dynamics, [942] MRI chemical shift, [297] Dixon acquisition, [297] excitation pulse design, [313, 337] excitation trajectory design, [291, 295] experimental design, [366] monohedral, [354] open magnet, [302] random trajectories, [1043] RF coil design, [279] multi-objective optimisation, [316] nerve fibre activity, [946] neural network, [1056] drug design, [100] drug testing, [897] fuzzy, [996] neural networks, [551, 563, 228, 565, 198, 460, 476, 966, 985, 1013, 570, 23, 45, 779, 85, 828, 1153, 893] neural networks Bayesian, [1011] cellular, [256] classification, [944, 215, 956, 961, 496, 517, 518, 1012, 578, 263, 1033, 634] control, [688] data mining, [258, 392] diagnosis, [205] drug design, [112] electronic nose, [1087] feature extraction, [575] fuzzy, [538, 240] hybrid, [135, 1032] image segmentation, [529] knowledge, [914] Kohonen, [552, 232] learning, [957] machine learning, [959] medical applications, [450] optimisation, [883] pattern recognition, [481, 595] perceptron, [1128] prediction, [930, 833] RBF, [1151] simulation, [605] SOM, [261] structure, [928, 164] taining, [947] training, [926, 462, 276, 1103, 858] traning, [496] walking, [1089] weights, [117] neural stimulation waveform, [705] neuroimaging MRI, [327] neurology, [1165] Alzheimer’s disease, [779, 805, 418] amyloid fibrils, [1158] BAEPS, [361] brain activity, [1086, 1157] brain imaging, [509, 266] brain oscillation, [866] brain oscillations, [904] brain stimulation, [1160] brainwaves, [1162] cancer, [773] dementia, [357] EEG, [145, 801, 1068] electrodes, [843] epilepsy, [149, 150, 143, 1034, 144, 146, 147, 148] fMRI, [404] hypoxia, [1056] ion chennel conductance modeling, [1159] lateral sclerosis, [854] lesions, [407] motoneurons, [977] nerve activity, [946] neural oscillations, [838] neuronal paths, [721] Parkinson’s disease, [339, 782] Parkinsonian oscillations, [900] prosthesis control, [667] rehabilitation, [1017] sclerosis, [800] sleep, [944, 961, 570] transcranial DC stimulation, [895] transcranial stimulation, [901] vestibulo-ocular reflex, [1029] vision, [1163, 1164] visual attention, [1161] neurons io channel modeling, [685] niche, [931] niche GA, [319] NIRS blood, [1060] microbes, [837] wavelength selection, [768, 1059] Subject index 55 NMR, [473, 506] brain imaging, [343] excitation pulse, [329] imaging, [529] NMR imaging, [442, 260] NOC, [803] nutrition variable selection, [795] oncology chemotherapy, [635] radiotherapy, [1092, 1093, 621, 626, 1096, 633, 665, 1045, 701] operating room scheduling, [661, 666] ophthalmology diabetes, [290] glaucoma, [652, 669] retinal imaging, [969] tumours, [780] opthalmology retinal imaging, [384] optical coherence tomography, [348] optics, [1069] skin, [774] skin imaging, [280] spectroscopy, [1065] optimisation diet, [637] multi-objective, [291, 630, 295, 646, 670, 214, 345, 360] multiobjective, [682] Pareto, [196, 718] optimization, [1141] global, [117] multi-objective, [531] Pareto, [931] oral cancer risk, [1125] orthopaedics arthritis, [834] bones, [804] orthopaedy implants, [663] paralled GA, [727] parallel GA, [155, 560, 566, 117, 1137, 967, 604, 163, 272, 275, 277, 822, 431] parallel GA grid, [309] PVM, [454] workstations, [249] parameter estimation, [1137] Pareto, [663, 345, 360] MRI, [291, 295, 297, 297] Parkinson’s disease, [619, 58] particle swarm, [688, 376] patent, [533, 572, 239, 243, 245, 247, 262, 600, 603, 265, 680] pattern recognition, [226, 507, 526, 578, 259, 1032] blood cells, [298] EEG, [320] FFT, [331] medical, [488] melanoma, [965] optic disc, [308] phoneme, [1155] tumor, [525] PBGA, [185] PCA, [357, 736, 746] classification, [709] penicillins, [36] peptides surfactants, [852] peptidome, [724] perceptrons, [578] pharmacokinetics model selection, [105] pharmacology, [135, 848] drug design, [21] toxicity, [586] pharmasy, [23] pharmocology, [50] physics bio-, [660] medical, [492, 499] molecular, [119] optics, [649] physiology, [966] brain hemodynamics, [776] cardiac transmembrane potentials, [746] cardiomyocytes, [783] eye movements, [1029] fatique, [890] glucose, [809] heart, [820] muscle fatigue, [1108] nutrition, [202] oximetry, [1115] Parkinsonian oscillations, [900] respiration, [406] thermoregulation, [715] vision, [221, 1088] voice, [1040] walking, [827] planning layout, [708] medical center location, [424] menu, [637] operating room, [666] plastic surgery, [683] therapy, [569] planning radiotherapy, [378] PLS, [719] pollution, [613] popular, [136] DNA breeding, [29] population multiple, [1079] population size, [168] 100, [226] post mortem dental identification, [15] prediction, [1038] breast cancer, [964] survival, [620] process fermentation, [728, 731, 110] 56 Genetic algorithms in medicine prostate implants, [1095, 615] protein docking, [142] protein engineering DNA breeding, [29] protein folding, [123, 129] amyloid fibrils, [1158] structure prediction, [844] protein folding?, [118] proteins, [119, 130, 136] 17-residue, [942] albumin, [642] apicoplast, [792] apolipoprotein epsilon4, [595] directed evolution, [24] docking, [923, 937, 967, 139, 140, 1023, 28, 764, 58, 83, 95] drug design, [125, 126] HIV-1 protease, [937] homology, [124] interactions, [1151] ligands, [438] proteome, [787, 836] purification, [97] QSAR, [968] recognition, [923] sequences, [777] signature, [1121] similarity, [1149] proteins folding, [1009] proteome hepatitis B virus, [763] proteomics cardiology, [703] PSO, [1120, 179, 428, 898] image registration, [1064] source location, [148] psychiatry dementia, [595] diagnosis, [571] psychology, [1167] biological, [645, 676] physiological, [287] psychotherapy, [978] pulmonary embolism, [647] puuttuu (ISI), [732] QSAR, [120, 1009, 141, 26, 634, 55, 64, 65, 70, 71, 76, 78, 89, 852, 101, 103, 877, 115, 116] QSAR drug design, [40, 96, 98] QSPR, [120, 114] QSRR blood, [767] QSSR, [897] quantum computing DNA, [159] radiation shielding, [823] radiation therapy geometry, [1133] radiography subtraction, [309] radiology, [941, 992, 999] beam angle, [1123] impedance, [717] implants, [1135] mammography, [733] planning, [718] thorax, [370] radiosurgery, [484] radiotherapy, [911] beam optimization, [654] images for, [453] implant, [603] IMRT, [1096, 633, 1044, 1045] intensity-modulated, [621, 665, 701, 1050] intesity-modulated, [1099] optimisation, [1106] planning, [1134, 584, 602, 1095, 615] reasoning case based, [743, 770] fuzzy, [990] recombination recursive, [24] registration retinal image, [969] regression, [120, 950, 1058] exponential, [704] linear, [860] logistics, [694] piecewise linear, [1145] PLS, [642, 51] radiation dose, [704] SVM, [66] regressions, [968] reliablility, [253] REM, [552] report on activities medicine, [590] retina, [1088] ICGA, [364] retinal imaging indocyanine green, [254] review biomedical applications, [515] computational intelligence, [222] Computer-aided molecular design, [131] GA in drug design, [128] image registration, [254] medical image registration, [432] medicine, [579] molecular design, [138] neuro-fuzzy rule generation, [240] of [162], [161] operating room scheduling, [690] urology, [933] robotics control, [320] grippers, [631] medical, [269] mobile, [185] routing, [682] rule based system, [489] Subject index 57 rule based systems, [449, 1084, 982, 991, 240, 609] medicine, [571] scattering, [1069] inverse, [774] scheduling chemotherapy unit, [1112] clinical pathways, [1129] operating room, [661, 666] vaccination, [1114] scheduling ¿/operating room, [690] screening diabetic retinopathy, [290] in silico, [32, 33, 47, 52, 61] virtual, [59] segmentation, [916, 529, 546, 239, 243, 245, 247] 3D, [327] CT, [365, 372] segmentation?, [490] selection biomarkers, [821] feature, [407] wavelength, [1060] sensing hearing, [610] tactile, [879] sensoring, [1087, 578] sensors tactile, [802] serum triglyseride, [768] shape design FEM, [808] shape model B-spline, [266] signal procesing medical, [538] signal processing, [555, 1080, 1139, 996, 346] brain, [866] classifiers, [500] compression, [1138] ECG, [956, 824, 431] EEG, [736, 801, 1068, 147, 148] electrocardiographs, [927] feature selection, [529] finger movements, [782] FPGA, [431] heart rate, [829] medical, [444, 493, 521, 536, 1034, 361, 375] multidimensional, [221] sEMG, [1108] speech, [645, 676] ultrasound, [427] visual to audio, [884] voice, [796, 845, 872, 1154, 1155] wavelets, [1033] signal processsig medical, [500] simulation, [1142, 557] catheter, [656] diffuse optical tomography, [325] NIR spectroscopy, [1158] surgery, [611] skin melanin, [774] skin modeling optical, [391] skull, [267] sleep apnoea, [1115] snakes, [502, 544, 546] SNP, [165] solid modeling, [958] SOM, [261] spectroscopy, [66] 2D correlation, [1158] biomedical, [519, 250] blood, [780] classification, [653] feature selection, [825] fitting, [1145] FT-IR, [207] gingival crevicular fluid, [862] impedance, [1102] infrared, [596] mass, [653, 813, 1121, 862, 863] mass-, [716] melanoma, [627] metabolomics, [725] NIR, [973, 597, 642, 650, 651, 548, 549, 693, 347, 1060, 825, 837] NIRS, [768] NMR, [519, 765] Raman, [207, 757, 1065] skin, [1039] wavelength selection, [596, 548, 549, 693, 1059, 773] splines, [692] sport muscle fatigue, [1108] sports clenbuterol, [831] SQUID, [618] Staphylococcus aureus Sortase A inhibitors, [82] statistics medicine, [858] stem cells biomarkers, [740, 821] stereo vision on-line, [692] strain testing arteries, [1030] implant, [641] structure molecular, [659] support vector machine, [355] surafaces superquadrics, [503] surgery, [352] liver, [1153] MRI, [302] operating room scheduling, [690] 58 Genetic algorithms in medicine planning, [592, 599, 382] plastic, [878] protatate, [625] radio-, [902] robotic, [879] sensoring, [802] simulation, [677] spinal, [356] vascular, [808] survey microarray data analysis, [208] pattern recognition, [208] SVM, [719, 37, 748, 753, 769, 65, 810, 416, 846, 1130, 856, 425, 864, 433, 898, 899] SVM classifier, [1161] feature selection, [1077] regression, [746, 873] synovial fluid, [834] system estimation, [975] telecommunications in hospitals, [1124] therapy UV, [619] thermography ocular, [385] ulcers, [368, 195, 1048, 390] thomography cancer, [365] time series Mackey-Glass, [959] medical, [316] tissue skin, [280] tissue perfusion ICG, [380] tomography, [198, 512, 523] brain, [275] CT, [315, 365] EIT, [1036] EMRI, [367] impedance, [459, 510] lung, [326] medical, [485] MR, [508, 344] NIR, [353] NMR, [958] OCT, [348] optical, [351, 353, 400] PET, [327, 344, 363, 374] reconstruction, [248, 270, 285, 317, 323, 334, 334, 338, 340, 350, 363, 374] SPECT, [270] Tikhonov regularization, [671] ultrasonic, [494] X-ray, [504] x-ray, [285] tomography elasto-mechanical, [323] TOPAS, [18, 19] toxicology environmental, [771] QSAR, [714] training surgery, [625] transplantation liver, [995] transportaion traffic, [883] tress, [880] TSP, [443] tutorial GA in drug design, [122] QSAR, [133] QSPR, [134] ultrasound, [561] bone, [267] urology, [489] USA, [1029, 1095, 615] vaccines allocation, [861] filoviral, [818] variable selection, [767, 68] regression, [694] vascular tree lung, [417] vectors mosquito, [1101] Yersinia pestis, [310] venoms snail, [942] virology influenza A, [836] virus, [885] dengue, [742] yellow fever, [955] vision early, [605] evoked potentials, [221] visualization palette design, [344] vitamin K, [942] VLSI FPGA, [345, 360] VLSI design, [593] voice assessment, [748] wavelength selection image, [196] NIR, [642, 651] NIRS, [973] wavelets, [470, 541, 318] voice, [748] Annual index 59 4.8 Annual index The following table gives references to the contributions by the year of publishing....

    [...]

  • ..., [291, 295] D’Alessandro, Brian, [400, 401] D’Alessandro, Maryann, [1034] Daliri, Mohammad Reza, [1119, 418] da Silva, Fernando Jose Mateus, [727] Damas, Sergio, [304, 321, 322, 386, 395, 421, 432] Dandekar, Omkar, [345, 360]...

    [...]

  • ...Abbotts, R., [747] Abdelwahab, Nada S., [816] Abdula, Ahmed Mutanabbi, [33, 47] Abdullah, Wan Ahmed K. Wan, [1064] Abdullah-Al-Mamun, Khondaker, [904] Abdul-Wahid, Christopher Badi’, [46] Abdul-Wahid, Sarah, [46] Abel, David L., [1116] Abolfath, R. M., [701] Abraham, Mannil Thomas, [758] Abramavicius, D., [1158] Abu Khalaf, Reema, [47] Accornero, N., [551] Acharya, R. S., [199, 917] Acharya, U. R., [908] Achim, Moise, [613] Acree, William E. Jr, [65] Adamec, J., [194] Adamopoulos, A. V., [607, 618] Adamopoulos, Adam, [723, 853] Adankon, Mathias M., [871] Adhikari, D., [696] Adhikari, Nilanjan, [877] Adiamah, Delali A., [786] Adjemian, J. C. Z., [310] Adjeroh, Donald, [16] Adler, Dorit D., [464, 940, 507] Afarideh, Hossein, [823] Afifi, Ahmed, [376] Afrasiabi, Mahlagha, [407] Afshari, Elnaz, [879] Agarwal, Shilpi, [767] Aghamohammadi, Hasan, [424] Aghamohammadi, Hossein, [424] Aghbashlo, Mortaza, [815] Aguilar, Guillermo, [1039] Aguilar, J., [520] Aguilar, R., [210, 1037] Ahmad, Fadzil, [1128] Ahmad, Sabbir U., [581, 1049] Ahmadi, T., [100, 113] Ahmadi-Roudi, Behzad, [767] Ahmad Noruddin, Nur Adelina, [34] Ahmed, M. N., [953] Ahmed, Mohamed N., [479] Ahmed, S., [479] Ahmed, Z., [1112] Ahrabian, H., [814] Aikimbayev, Alim, [711] Ainon, Raja Noor, [1113] Ait-Aoudia, Samy, [333, 349] Aizenberg, I., [256] Aizenberg, N., [256] Akhtari, M., [461] Akyuz, Lalehan, [101] Alam, M. S., [1110] Alander, Jarmo T., [693, 347, 548, 549, 1016, 1017, 1018] Alavikia, Zahra, [1124] Alayón, S., [210, 1037] Al-Azzawi, Nemir, [1064] Albani, C., [943, 978] Albertelli, L., [979] Alderliesten, Tanja, [656] Alektiar, K. M., [569] Alghisi, Federico, [787] Algoul, S., [1110] Al-Horani, Rami A., [79] Ali, Fath El Alem Fadlallah, [487, 543] Ali, Fath El Alem F., [497] Ali, Hamed I., [58] Al-Ijel, Hebah, [61] Alkhalifa, A. Y., [202] Allen, S. J., [827] Almasganj, Farshad, [748, 1154] Al-Mulla, Mohamed R., [1108] Al-Nadaf, Afaf H., [32] Al-Najjar, Belal O., [34] Alolfe, Mohamed A., [313] Alolfe, Mohammed A., [329] Alqtaishat, Saja, [93] Al-Rawi, Mohammed, [1041] Alvarez, Daniel, [1115] Alves Honório, Nildimar,[679] Aly, Nabil M., [339] Amari, Sun-ichi, [552] Amaritsakul, Yongyut, [894] Amaro, Ana, [1076] Amburn, Philip, [239, 243, 247, 262, 533] Ames, Forrest, [368, 195, 1048] Amin, H., [326] Amirzadi, Azardokht, [422] Ammar, Hany, [16] Amols, Howard I., [1095] Analoui, Mostafa, [17] Anand, Christopher Kumar, [1043] Anastasio, M. A., [492, 531] Anastasio, Mark A., [206] Anastassopoulos, George, [723, 853] Anbarasu, L. A., [187] Andalib, Elham, [880] Anderson, Jonathan D., [692] Anderson, Julie, [368, 195, 1048] Anderson, R. W., [183] Anderson, William S., [866] Andersson, L., [158] Andersson-Engels, Stefan, [780] Andonie, Razvan, [46] Andrews, B. J., [1007] Andris, Peter, [506] Anekboon, Khantharat, [903] Angel, Pedro L. de, [260] 18 Genetic algorithms in medicine Angeles, Jorge, [802] Angeletti, Cesar, [638] Angeline, Peter J., [981, 988] Anger, Lennart T., [63] Ankley, Gerald T., [174] Annane, Djillali, [867] Anninos, P. A., [607, 618] Anon., [120, 136] Antonets, Denis V., [850] António, Carlos Conceição, [808] Anxolabéhère, Dominique, [160] Ao, Lu, [889] Aoki, Mikio, [794] Aoki, Shunsuke, [109] Arafuka, M., [914] Arakaki, Kouichi, [472, 483] Arámbula Cośıo, F., [625] Archetti, Francesco, [678] Archibald, James K., [692] Arciniegas, Fabio, [26] Arif, M., [317, 334, 334, 338, 340, 350] Arif, Muhammad, [396] Arnardottir, Helga Bjork, [788] Arnold, Mark A., [973] Arslanian-Engoren, Cynthia, [675] Arus, C., [456] Asadabadi, Ebrahim Barzegari, [883] Asadollahi, Tahereh, [52] Asadollahi-Baboli, M., [70] Ashayer, Sahar, [823] Askari, Mansur, [823] Asvestas, P. A., [268] Ataullakhanov, Fazoyl I., [35] Aukee, Pauliina, [982] Aung, Min S. H., [1047] Auramo, Yrjö, [591] Austin, E. M., [655] Autere, Antti, [693] Aviv, Amit, [822] Aylward, S., [191] Azam, Faizul, [58] Azar, Ahmad Taher, [1074] Aze, Jerome, [764] Azmi, Reza, [422] Azok, Joseph, [703] Baba, Roshidad, [774] Babu, Sainath, [84] Badea, Radu, [753] Bael, P. Van, [586] Bagchi, Manish C., [51] Bai, Baodong, [354] Bai, Li, [835] Bai, Lihua, [864] Bajcsy, Ruzena, [773] Baker, J. A., [469] Baker, Philip N., [653, 752] Bakhshali, Mohamad Amin, [1118] Bakhtiari, Mohammad, [1099] Bakken, Russell R., [818] Baldi, Fabio, [644] Baleja, James D., [942] Balestra, Gabriella, [825] Ballerini, Lucia, [212, 624, 293, 296, 502, 530, 544, 546, 547] Baltas, D., [612, 614, 1140, 1002] Baltazar, Rosario, [806] Baluja, S., [974] Bamer Natavan, Zahra, [875] Band, Beatriz Fernande, [870] Bandaru, Sunith, [369] Bandholtz, Sebastian, [85] Bandyopadhyay, Sanghamitra, [87, 886] Bandyopadhyay, Somnath, [789] Banghua, Yang, [320] Bansal, A., [1156] Banzhaf, Wolfgang, [258] Bardossy, Gergely, [730] Barik, S. K., [696] Baringhaus, Karl-Heinz, [63] Barker, Grant I., [46] Baroni, Guido, [878] Baronti, Flavio, [166] Barrios, Victor, [223, 224] Barros de Aguiar, Ducinéia, [679, 684] Barry, A. M., [1166] Bartenstein, P., [446] Bartholomay, Lyric C., [702] Bartlett, Karen, [710] Baskar, Gurunathan, [731] Baskent, Deniz, [676] Bast, T., [1003] Bast, Thomas, [150] Bates, Paul A., [42] Bates, S., [1112] Bath, P. A., [577] Bathen, Tone F., [1063] Battezzato, Alessandro, [1100] Bauer, J. T., [1097] Baum, K. G., [737] Baum, Karl G., [312, 328, 344] Baumgart-Schmitt, R., [944, 961] Bavilacqua, A., [249] Baylink, D. J., [989] Bazhan, Sergei I., [850] Beatty, P. C. W., [578] Becker, Kay, [912] Beckerman, Barbara G., [698] Beckett, L., [310] Beebe, N. W., [1097, 674] Belani, Chandra P., [57] Beliën, Jeroen, [690] Beligiannis, G. N., [607, 618] Beloufa, Fayssal, [1070] Benavent, Antonio Penalve, [419] Benche, I., [290] Bencic, David, [174] Bendahl, Par-Ola, [858] Benedetti, Manuel, [314] Benedict, Mark Q., [686] Benezeth, Y., [799] Ben-Jacob, Eshel, [809] Bennett, Kristin P., [26] Bennett, Kristin, [27] Ben-Shalom, Roy, [822] Berg, Patrick, [150] Authors 19 Berg, P., [1003] Bergen, Stuart W. A., [1049] Berger, Martijn P. F., [776] Berkey, Telford S., [239, 243, 247, 262, 533] Bernardes, Joao, [1127] Bernardo, Marcelino, [414] Bernaschi, Massimo, [1144] Bernauer, Julie, [764] Bertrand, Louise, [301] Bes, F., [944] Best, J. A., [662] Bevilacqua, A., [604] Bevilacqua, V., [294] Bevilacqua, Vitoantonia, [378] Bezerianos, A., [221] Bhat, Ajita Atul, [124] Bhat, Shekara, C. Chandr, [830] Bhatia, Manish S., [76] Bhatt, Hardik G., [64] Bhattacharya, Mahua, [330, 381, 388, 398] Bhattacharyya, Malay, [886] Bhattacharyya, Shuvra S., [345, 360] Bhhatarai, Barun, [714, 771] Bi, Chengpeng, [1150] Biales, Adam, [174] Bickel, Arthur S., [1141] Bickel, Riva Wenig, [1141] Bidaud, Philippe, [269] Bies, Robert R., [57] Bigdeli, H., [970, 983] Bijar, Ahmad, [419] Bindl, G., [1020] Bini, M., [510] Blackburn, Jason K., [681, 711] Blackburn, Jason Kenna, [668] Bladen, K. R., [253] Blanchet, Max, [552] Blazewicz, Jacek, [907] Bloy, Luke, [335] Bocchi, L., [212, 624, 296] Bodén, Ida, [548, 549] Bofin, Anna, [1063] Bogacz, Rafal, [900] Bogdan, Malgorzata, [788] Boggs, Sarah R., [1121] Bogolyubov, Alexey A., [35] Bohle, Kathrin, [728] Boisvert, Michel R., [812, 840] Bojan, Vinoth Kumar, [146] Bojarczuk, Celia C., [620] Bolboaca, Sorana D., [102] Bonelli, Pierre, [553] Bong, Chin Wei, [403] Bonnet, A. S., [1073] Booth, V., [977] Borovskaia, A. D., [712] Bosman, Peter A. N., [656] Bot, Corina T., [783] Boughton, Edward M., [926, 947, 981, 988] Bouma, Brett E., [660, 348] Bourgeois-Republique, C., [639] Bourgeois-Republique, Claire, [687] Bourgeois-République, Claire, [375] Bourquard, Thomas, [764] Bower, M., [1004] Braaten, Øivind, [157] Braaten, O., [1027] Brameier, Markus, [258] Brandt, Carlos A., [39] Brasacchio, J. B., [1014] Brasacchio, R. A., [993] Brauer, Matthew J., [163] Bredno, Joerg, [235] Breinig, M., [665] Brendel, Bernhard, [352] Breneman, Curt M., [26] Breneman, Curt, [23, 27] Brener, Nathan, [384] Brennan, Marie-Luise, [703] Bressloff, Neil W., [754] Brest, J., [583, 1010] Breuer, Arnon, [1145] Brezocnik, Miran, [657] Brezovich, Ivan A., [704] Briceno, Javier, [1153] Broadhurst, David I., [752] Brooijmans, Natasha, [28] Brors, Benedikt, [886] Broschat, Shira L., [792] Broussard, Randy P., [239, 243, 245, 247, 262, 265, 533] Browder, Kathy, [688] Brown, J. Q., [649] Brown, J. Quincy, [426] Brown, Marie, [752] Brown, Richard, [1134] Brown, T., [706] Brudermann, U., [554] Brueckner, Adrian, [652] Brugger, S., [1071] Brunauer, Leonhard, [331] Brunner, Stephen, [1099] Brunsdon, Chris, [708] Brusic, Vladimir, [135] Bulgiba, Awang, [1113] Burlinson, S., [595] Burman, Jerry A., [526] Burnham, K. J., [919, 934, 954, 971] Burns, A., [595] Burns, David H., [812, 840] Burrezo, S., [592, 599] Bursell, E. S., [290] Burton, Dean, [743] Buscema, Massimo, [644] Butte, Atul J., [1152] Butylin, Andrey A., [35] Caballero, Julio, [43] Caballero-Morales, Santiago-Omar, [1155] Cabrera-Perez, Miguel Angel, [90] Cadieux, S., [474] Cagnoni, Stefano, [689, 916, 1081, 523] Cai, Hai-yan, [53] Cai, H., [559] Cai, Jian-Fang, [716] 20 Genetic algorithms in medicine Cai, Wenli, [1111, 416] Cai, Xi, [868] Cajko, Frantishek, [1160] Calafate, Carlos T., [869] Caldwell, Craig, [1167] Callaghan, Vic, [806] Calonaci, Cristiano, [1114] Cameron, George G., [454, 468, 477, 958, 488] Campanini, R., [249, 604] Campbell, J. A., [536] Campo, Felix De, [1115] Canal, M. Rahmi, [144] Candavelou, Manimozhi, [844] Cannings, C., [1156] Cano, Juan-Carlos, [869] Canseven, A. G., [673] Cao, Hua, [342, 359, 384] Cao, Maria D., [1063] Cao, Wenhua, [1123] Caorsi, Salvatore, [246] Capozza, M., [551] Cardoen, Brecht, [690] Carlborg, O., [158] Carlsson, Lova, [654] Carmack, Patrick S., [785] Carnahan, B. J., [962] Carpaneto, Jacopo, [1105] Carpenter, T. A., [442, 452, 473, 524] Carroll, D. L., [499] Carvalho, P. d, [1057] Carvalho Filho, Antonio Oseas, [434] Castañeda, Miguel A. Padilla, [611] Castellano, Pilar, [260] Castellanos, N. P., [284] Castiglione, Filippo, [1144] Castro, Catarina F., [808] Castro, Jesus Silva, [927] Catalogna, Merav, [809] Cazares, Lisa H., [1121] Celi, Leo A., [859] Celi, Leo Anthony, [867] Cerdan, S., [456] Ceres, Ramon, [1077] Cestari, Renzo, [644] Cevik, A., [673] Cha, Kyung-Joon, [1117] Cha, Soonmee, [773] Champion, H., [1106] Chan, Christina, [856] Chan, Heang-Ping, [457, 464, 940] Chan, Kelvin, [1072] Chan, Yung-Kuan, [402] Chanda, B., [332] Chandy, D. Abraham, [308] Chang, Hsueh-Wei, [720, 1125, 178] Chang, R., [928] Chang, Shih-Fu, [703] Chang, Siow-Wee, [758] Chang, Susan M., [773] Chang, Yuan-Hsiang, [985, 986, 1011, 1013, 542, 545] Chao, C. L., [655] Chao, Ching-Kong, [663, 894] Chao, Chun Cheih, [722] Chao, Yuyan, [370] Chapman, Brian E., [394, 417] Chapman, Christopher Neal, [571] Chaturvedula, Ayyappa, [848] Chau, Tom, [735] Chaves, Rui, [808] Chen, Ai-ting, [726] Chen, Bae-Horng, [459] Chen, Beibei, [889] Chen, Biyun, [855] Chen, Chien-Cheng, [130] Chen, Chuchu, [768] Chen, Ding-Horng, [217] Chen, Gongxing, [1152] Chen, Hongmei, [864] Chen, Houjin, [324] Chen, Hsiang-Yin, [995] Chen, Hui, [719, 99] Chen, J. D. Z., [486] Chen, Jiakai, [834] Chen, Jiann-Jone, [436] Chen, Jianquan, [140] Chen, Jiejing, [1122] Chen, Jinxia, [893] Chen, Kaixian, [128] Chen, L. Leon, [866] Chen, Liangbiao, [648] Chen, Li-Li, [836] Chen, Mingyang, [430] Chen, Peiqi, [874] Chen, Qiu-Yan, [1065] Chen, Ran, [768] Chen, Rong-Tai, [402] Chen, Shanshan, [890] Chen, Ta-Cheng, [995] Chen, Wei, [147] Chen, Wen-Chin, [130] Chen, Wen-Pin, [691] Chen, Xiao Yu, [891] Chen, Xiaofen, [834] Chen, Xiao-Lu, [833] Chen, Xiaowen, [769] Chen, Yazhu, [303] Chen, Y., [589, 1096, 938, 941] Chen, Yen-Hung, [218] Chen, Yen-ting, [514, 540] Chen, Yen-Wei, [466, 472, 483, 487, 490, 497, 543] Chen, Yi, [368, 195, 1048, 390] Chen, Yihan, [864] Chen, Yuehui, [1151] Chen, Yuelei, [62] Chen, Yu-Jung, [720] Chen, Zhongxue, [177] Cheng, G., [585] Cheng, Heng-Da, [218] Cheng, J. C. Y., [244] Cheng, Jian, [180] Cheng, Kuo-Sheng, [459] Cheng, Kuo-sheng, [514, 540] Cheng, Shu-Chen, [1035] Authors 21 Cheng, Yuh-Min, [1032] Cheng, Yu-Huei, [781, 1125, 839, 181] Cheng, Zhi-Bin, [835] Cheriet, Farida, [871] Chettri, A., [696] Chetty, Madhu, [172, 817] Cheu, Wen-Chin, [119] Cheung, R., [325] Chew, Lita, [749] Chi, Hanlin, [140] Chiacchio, Ferdinando, [1114] Chiang, Cheng-Yu, [1162] Chihab, Najat, [871] Chikh, M. A., [1070] Chikh, Mohamed Amine, [1107] Chilov, Ghermes G., [59] Chippindale, Adam K., [162] Chitre, Yateen, [455] Chiu, Hung-Wen, [739] Chiu, Ming-Jang, [147] Cho, Sung Jin, [123] Choi, Bernard, [1039] Choi, Chulhee, [380] Choi, H., [325] Choi, Tae-Sun, [413] Chong, Chiet Sing, [664] Chongstitvatana, Prabhas, [431] Choonara, Yahya E., [106] Chou, You-Li, [1032] Choudhari, Prafulla B., [76] Chow, Chi Kin, [252] Choyke, Peter L., [414] Christini, David J., [783] Chu, C., [666] Chu, Na, [891] Chuang, Chih Yuan, [739] Chuang, Li-Yeh, [720, 741, 781, 807, 1125, 839, 842, 178, 181] Chuang, Yung Jen, [722] Chui, Chee-Kong, [865] Chun, Se-Hak, [770] Chung, Bevan Kai-Sheng, [777] Chung, Hyun-Tai, [902] Cilingir, Gokcen, [792] Cinsdikici, Muhammed G., [435] Ciofani, Gianni, [1105] Ciuca, I., [215] Clague, J. E., [577] Claridge, Ela, [280, 282, 283, 289] Clark, David E., [131, 138] Clark, Kevin Patrick, [126] Clark, Taane G., [658] Clarke, L. P., [1083, 534] Clarke, Laurence P., [463] Clavel, Jacqueline, [762] Clegg, J., [798] Clement, Greg T., [267] Clemmer, D. E., [813] Clifford, Gari D., [867, 906] Coen, Muireann, [765] Cohen, A., [521] Cohen, Eyal, [809] Cohen, G., [237] Colaninno, A., [294] Coley, D. A., [539] Collet, Pierre, [288, 639, 687, 375] Colley, M., [1108] Collins, Matthew J., [804] Collins, Steve M., [448, 465, 230] Colombetti, Marco, [201] Comber, Alexis J., [708] Comely, Richard, [910, 437] Congdon, Clare Bates, [918] Connor, Christopher W.,[267] Constantin, Alexandra, [773] Cook, Robert G., [1163, 1164] Cooper, R. D., [1097, 674] Coppel, Ross, [817] Copur, Fatih, [36] Cordes, Dietmar, [404] Cordón, Oscar, [304, 321, 386] Cornett, Ben, [789] Correa, Elon, [725] Correa, Esteban M., [736] Correia, Mauro M., [382] Cosio, C. F., [987] Coşkun, Aysun, [659] Cośıo, Fernando Arámbula, [611] Costa, Lino, [1077] Costard, Anne D., [168] Cotrutz, C., [621] Coutinho, M.S., [948] Crampton, Jason, [336] Craw, Susan, [743] Crilly, Paul B., [555] Cristea, A., [215] Crozier, Stuart, [746] Cruz-Ramirez, Manuel, [1153] Cui, Lizhi, [874] Cui, Yaoyao, [1031, 980] Cull, A., [1106] Cunxi, Chang, [372] Curran, Tim, [404] Curtis, Andrew Thomas, [1043] Curtis, Andrew, [681] Curzen, Nick P., [754] Cutler, Gene, [648] Cytowski, Jerzy, [475] Czarnecki, C. A., [453] D’Addabbo, A., [294] Dadfarnia, Shayessteh, [52] Dagdeviren, Zuleyha Akusta, [435] Dai, Chunni, [196] Dai, Jianrong, [584] Dai, Yong, [1122, 834] Dai, Zong, [836] da Costa Filho, Paulo A., [597] da Costa Gurgel, Helen, [679, 684] Dale, Brian M., [291, 295] D’Alessandro, Brian, [400, 401] D’Alessandro, Maryann, [1034] Daliri, Mohammad Reza, [1119, 418] da Silva, Fernando Jose Mateus, [727] Damas, Sergio, [304, 321, 322, 386, 395, 421, 432] Dandekar, Omkar, [345, 360] 22 Genetic algorithms in medicine Dandekar, Thomas, [601] Dansereau, Jean, [871] Darbandi, Mohammad Ali, [104] Darby, I. B., [862] Darenfed, Salah, [198] Dargahi, Javad, [802] Darwish, Hany W., [66] Das, Arpita, [330, 381, 388, 398] Das, Shiva K., [694] Dasgupta, Suman, [332] Dashtbozorgi, Zahra, [65] Datz, F. L., [925] David, E., [567] David, Florian, [728] Davies, B. L., [987] Davoodi, R., [1007] Dean, David, [1093, 626] Deb, Kalyanmoy, [369] Deckers, Jozef, [695] DeGroote, John P., [702] Dehmeshki, Jamshid, [326] Dekker, L. V., [747] de Araújo, Aurigena Antunes, [1059, 1060] de Arruda, Mércia Eliane, [679, 684] De Chierico, Federica, [787] Delgado Atencio, Jose Alberto, [1069] Delibasis, Konstantinos K., [254, 268, 440, 454, 468, 477, 958, 488, 969, 1088] De Iorio, Maria, [658] Del Angel, P. L., [284] de Lima, Kassio Michell Gomes, [1060] de Moya, Marc, [416] de Oliveira Neves, Ana Carolina, [1059, 1060] Delp, Edward J., [17] de Paiva, Anselmo Cardoso, [434] de Sampaio, Wener Borges, [434] Delsanto, P. P., [494] Delzell, Darcie A. P., [785] Demeulemeester, Erik, [690] Demiris, E. N., [607, 618] Demoury, Claire, [762] Deng, Youping, [177] Denton, Brian T., [784] Desai, D., [665] Desai, Umesh R., [79, 107] Deshmukh, A. Y., [411] Deshmukh, C. N., [371] Deshpande, Shreekant, [49] Desimo, Martin P., [239, 243, 247, 262, 533] Devcic, Zlatko, [691] Devogelaere, D., [586] Devogelaere, Dirk, [27] Dexter, Tim, [851] Dhaenens-Flipo, Clarisse, [623] Dhar, Sulochana, [426] Dhawan, Atam P., [351, 400, 401, 439, 455, 556, 228] Diao, Xiaodi, [1129] Dias Vasconcelos, Simão,[679, 684] Dillon, N., [442, 452, 473] Di Martinelly, C., [661] Dimarki, T., [578] Dimiziani, Leopoldo, [787] Dinevski, D., [383] Ding, Qing, [973] Dinov, Ivo D., [327] Diong, B., [632] Distefano, G., [551] Dixit, Swati R., [411] Dobrzeniecki, A. B., [916, 523] Doerner, Karl, [682] Dogrusoz, Yesim Serinagaoglu, [1132] Doi, K., [460, 492] Dokur, Z., [516, 541] Dokur, Zümray, [1033, 276] Dominici, Patrizia, [644] Donelli, Massimo, [314] Dong, Huiqing, [800] Dong, Jinxiang, [319] Dong, Ling, [763] D’Onofrio, David J., [1116] Dony, Robert D., [192] Doorn, Nienke L. va, [804] Dorado, Julian, [462] Douglas, T. S., [274, 495] Douglas, Tania S., [513] Douguet, Dominique, [18] Doyle 3rd, Francis J., [715] Doytchinova, Irini, [91, 94] Drake, Richard, [1121] Dréo, Johann, [311, 364] Dries, Laurie A., [163] Drosos, Georgios, [853] Du, Fuli, [601] Du, Gang, [1129] Du, Jiang, [885] Du, Juan, [40] Duan, Huilong, [505] Dubel, Stefan, [728] Duca, J. S., [994] Duerk, Jeffrey L., [291] Dumont, Georges, [269] Dunn, Warwick B., [653, 752] Duraipandian, Shiyamala, [757] Durant, E. A., [610] Durant, Eric A., [610] Durbin, Dennis R., [576] Dutta, P. K., [305] Dutta, Pranab K., [755] Duvic, Madeleine, [627] Dwayne, Harlan J., [84] Dybowski, R., [928] Dye, John M., [818] Dyke, J., [237] Ebadi, Ahmad, [74] Ebbels, Timothy M. D., [765] Eberhart, Russell C., [222, 515] Eberl, Stefan, [357] Echauz, Javier, [1034] Edelvik, Fredrik, [148] Eden, Patrik, [858] Edirisinghe, C. D., [199, 917] Edraki, Najmeh, [71, 74] Edwards, Brent, [676] Authors 23 Egorin, Merrill J., [57] Eiler, Cheryl L., [676] Eilers, R., [944, 961] Eils, Roland, [886] Ekbal, Asif, [420] El-Baz, Ayman, [278] Eldeib, Ayman M., [522] Elketroussi, Mehdi, [1079, 557] Elkhaled, Adam, [773] Elkorany, Abeer Mohamed, [1074] El-Kwae, Essam A., [498] Ellis, David I., [653] Elmekkawy, Ty, [1112] Elsen, Jean-Michel, [168] Elshazly, Hanaa Ismail, [1074] Elveren, Erhan, [1103] Embrechts, Mark J., [26, 27] Embrecths, Mark J., [23] Emile, J. F., [799] Endo, Tokiko, [445] Engoren, Milo C., [675, 1001] Erfania Saeedi, Nafise, [1154] Ergun, Ucman, [1053] Esteller, Rosana, [1034] Estévez, J., [210, 1037] Evans, D. J., [248] Evans, David J., [275, 277] Ezzell, G. A., [574] Ezzell, Gary Allen, [911, 1133] Fabregas, Carmen De Sola, [508] Fabry-Asztalos, Levente, [46] Fagan, Michael J., [778] Falgout, Barry, [742] Falk, Robert, [278] Fallah, Ali, [790] Fan, David P., [1079] Fan, Xiao-Hong, [716] Fan, Yi, [968] Fan, Yong, [272, 275, 277] Fang, Guanghua, [62] Fang, Jianwen, [38] Fang, Kuang-nan, [744] Fang, Liang, [423] Fang, Yuotong, [302] Farag, Aly A., [278, 479, 953, 481, 511, 537] Farag, Aly, [522] Farfán, J., [592, 599] Farman, Allan G., [537] Farmany, Abbas, [92, 897, 112, 114, 115] Farrall, Martin, [658] Fasinu, Pius, [106] Fassihi, A., [103] Fassihi, Afshin, [41, 81] Fatemi, Mohammad H., [772] Fathi, Madjid, [912] Faulkner, Graeme, [443] Fei, H., [666] Feiglin, Ariel, [316] Feiglin, David H., [328] Feitosa, Raul Q., [382] Felton, Michael J., [25] Fen, Ping, [197] Feng, Dagan, [357] Fenimore, Paul W., [818] Fereydouneyan, F., [1104] Fereyduni, Ehsan, [767] Ferguson, Allan M., [141] Fernandes, Joao Paulo S., [39] Fernandez, Jaime J., [444] Fernandez, Juan Carlos, [1153] Fernandez, Leyden, [43] Fernandez, Michael, [43, 810] Fernando, Chrisantha, [721] Ferno, Marten, [858] Ferreira, Elizabeth I., [39] Feyaerts, Maxim, [860] Fiege, J., [1106] Figlerowicz, Marek, [907] Fikry, Karim, [416] Filipič, Bogdan, [250] Fiorini, Paolo, [677] Firoozabadi, Mohammad, [824] Fiscarelli, Ersilia, [787] Fischer, Andrew H., [638] Fischer, Gary W., [995] Fischer, P. M., [747] Fischer, William M., [818] Fisher, B. J., [442, 452, 473, 524] Fisher, M. H., [919, 934] Fishman, Sigal, [809] Fitzgerald, Matthew B., [872] Fitzpatrick, J. Michael, [225, 204] Fiveash, John B., [704] Flask, Christopher Alan, [297] Flick, Robert, [174] Flotzinger, D., [913] Floyd, C. E., [469, 964] Focke, Axel, [682] Fogel, David B., [920, 923, 926, 947, 981, 988, 558] Fogel, Lawrence J., [923] Fogue, Manuel, [869] Foley, Brian T., [818] Foley, D. H., [706] Foley, Desmonf H., [1098] Foley, J. E., [310] Fonseca de Camargo Neves, Vera, [628] Fontana, Carolina, [847] Foroumadi, Alireza, [71] Forster, Carola, [108] Foster, James A., [20] Fotopoulos, S., [221] Fox, Michael D., [901] Frachet, Bruno, [639, 687, 375] Franco-Lara, Ezequiel, [728] Franzén, L., [293] Fraser, A. S., [151, 152] Frederick, E. D., [964] Freedman, M. T., [476] Freer, Stephan T., [923, 937] Freitas, Alex A., [620] Friedman, G. J., [153] Friend, Stephen H., [968] Frizera, Anselmo, [1077] Froeyen, Mathy, [90] 24 Genetic algorithms in medicine Frollo, Ivan, [506] Frolund, Sidsel, [50] Frommlet, Florian, [788] Fu, J. C., [343] Fu, Kuang, [405] Fu, Xiao-Hua, [833] Fu, Yanhua, [868] Fucharoen, Suthat, [903] Fuellen, Georg, [740, 805, 821] Fujita, Atsuto, [60] Fujita, H., [264, 485, 504, 512] Fujita, Hiroshi, [445] Fukui, Yasuhiro, [630, 646, 670] Fulham, Michael, [357] Funakubo, Akio, [630, 646, 670] Fung, Albert Y. C., [569, 1095, 615] Furie, Barbara C., [942] Furie, Bruce, [942] Furst, Jacob, [408] Furuhashi, Takeshi, [185] Fuss, R., [234] Fyfe, Murray, [710] Gaál, B., [1146] Gal, B., [637] Galeano, J., [799] Galiatsatos, Dimitrios, [853] Gallagher, R. J., [992] Gallego, M. J., [957] Galvan, Stefano, [677] Galvin, J. M., [1096] Gammerman, Alex, [1051] Gandy, S., [539] Gangl, Alfred, [331] Ganjali, Mohammad Reza, [37] Ganjtabesh, Mohammad, [814] Gant, V., [928] Gao, Bi-Xia, [716] Gao, Jin, [835] Gao, Lidong, [855] Gao, Nan, [182] Gao, Qinghui, [819] Gao, Yang, [429] Garćıa, A., [599] Garcia-Uribe, Alejandro, [627] Garg, Rajni, [707] Garǵıa-Armengol, Juan, [697] Garǵıa-Herrera, G., [592, 599] Garrido, J., [599] Garrido, Mariano, [870] Garrido, Piedad, [869] Garway-Heath, David, [336] Gasem, Khaled A. M., [86] Gaspar, L., [574] Gaspin, Christine, [186] Gastaldi, Laura, [1100] Gasteiger, Johann, [21] Gattass, Marcelo, [434] Gaughan, Patrick, [339] Gaunt, M. W., [955] Gavgani, Alireza Mazloumi, [1132] Gaye, M. M., [813] Gayou, Olivier, [694] Gayzik, F. Scott, [729] Ge, Xinna, [169] Gecen, Nazmiye, [36, 73] Gee, J., [191] Gefen, Smadar, [301] Gehlhaar, Daniel K., [923, 937] Geladi, Paul, [548, 549] Genever, Paul G., [778] Ghasemi, Jahan B., [52, 68] Gholami, Maryam, [81] Gholivand, Mohammad B., [41] Gholivand, Mohammad-Bagher, [905] Ghorai, Santanu, [755] Ghosh, Payel, [315] Ghosh, S., [580] Ghost, M. K., [305] Giegerich, Clemens, [63] Giger, M. L., [460] Giger, Maryellen L., [206, 478] Gilbert, F., [922] Giller, C. A., [718] Girault, Jean-Marc, [427] Girvetz, E....

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  • ...Shehadehh, Mayyada, [61] Shekhar, Raj, [345, 360]...

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  • ...H:, [310] Giuca, Anne-Marie, [408] Glen, Robert C., [139] Glendening, C. D., [994] Goebel, Rainer, [776] Goh, Carolyn, [1075] Goh, Gerard Kian-Meng,[20] Goicoechea, Hector C., [905] Goldammer, E. von, [567] Goldfarb, Lev, [22] Golla, Sharath, [86] Gollapalli, Sowjanya, [844] Golmohammadi, Hassan,[65] Golpayegani, Mohammad Reza Hashemi, [824] Golubitsky, Oleg, [22] Gomes de Lima, Kássio Michell, [1059] Gomez, Juan D., [736] Gomez, Luis, [1160] Gondos, Tibor, [730] Gong, Dunwei, [890] González, Fabio, [309] Good, Walter F., [985, 986, 1011, 1013, 542, 545] Goodacre, Rouston, [207] Goodacre, Royston, [725] Goodarzi, Mohammad, [49] Goodsitt, Michell M., [464, 940, 507] Gopal, Jeyakodi, [844] Gorbatenko, Aleksander S., [35] Gordón, Oscar, [322, 395] Goreti Rosa-Freitas, Maria, [679, 684] Gorges-Schleuter, Martina, [154, 155] Gotshall, Stanley, [688] Gottvald, A., [519] Goujon-Bellec, Stephanie, [762] Gould, E. A., [955] Goulermas, John Y., [1047] Gourinath, Samudrala, [67] Govindan, Sapna, [859] Govindarajan, Sridhar, [24] Authors 25 Govorun, V. M., [712] Graham, Allan MacKenzie, [327] Gramatica, Paola, [714, 771] Grassy, Gérard, [18] Gray, H. F., [456] Grbic, Anthony, [1160] Grebe, Reinhard, [220] Green, Darren V. S., [31] Grefenstette, John J., [204] Gribbestad, Ingrid S., [1063] Gribkova, Irina V., [35] Griffiths, Robert C., [658] Grill, Warren M., [705, 843] Grosman, Benyamin, [715] Grossi, Enzo, [644] Grotzinger, Carsten, [85] Grozier, S., [279] Grudinina, S. A., [712] Grujicic, M., [655] Grunhut, Marcos, [870] Gruss, Michelle Z., [717] Gu, Yi-Xin, [724] Gu, Yunyan, [889] Guan, Qiu, [820] Guanghua, Chunyan Li, [143] Gu∂mundsson, Markús, [498] Gubernator, Klaus, [132] Güç, Melikali, [214] Guerriero, S., [908] Gui, Gerald P. H., [851] Gulinck, Hubert, [695] Gulten, Gulcin, [109] Gunst, Richard F., [785] Guo, M. Z., [171] Guo, T., [852] Guo, Xiaoying, [768] Guo, Xin, [169] Guo, Zheng, [889] Guo, Zhou-Yi, [1065] Guojun, Bao, [528] Guozheng, Yan, [320] Gupta, Vinod Kumar, [767] Gur, David, [717, 1102, 542, 545] Guraksin, Gur Emre, [1053] Gurkiewicz, Meron, [685] Gururaja, K. V., [751] Gussregen, Stefan, [63] Gutjahr, Walter J., [682] Guyot-Goubin, Aurelie, [762] Haas, O. C. L., [919, 934, 954, 971, 1005] Hadaya, Nir, [316] Hadizadeh, Farzin, [98, 104] Häfner, Michael, [331] Haghjoo, Majid, [824] Hahn, Lance W., [164] Halasz, Gabor, [730] Halder, Amit Kumar, [96, 877] Haley, Robert W., [785] Hall, L. D., [442, 452, 473, 524] Hall, L. O., [1083, 534] Hall, Lawrence O., [463] Halliday, David M., [339] Halloran, M. Elizabeth, [861] Halpern, Zamir, [809] Hämäläinen, Matti, [1157, 936, 1086] Hamarneh, Ghassan, [273, 306] Hamdy, Shaheen, [1047] Hammer, Jürgen, [135] Hammoud, Z. T., [813] Han, Chao, [863] Han, Jung Ho, [902] Handels, H., [965, 525] Handschuh, Sandra, [21] Hani, Ahmad Fadzil M., [774] Hao, Ming, [44] Haque, M. Ehtashamoul, [393] Hara, Takeshi, [445] Hara, T., [264, 485, 504, 512] Harada, H., [975] Harboun-Cohen, Esther, [687] Härkonen, Henna H., [732] Harris, M., [1057] Harrison, Leonard C., [135] Hart, Mary Kate, [818] Hart, William E., [142] Hart, William Eugene, [117] Harvey, Neal R., [638] Hasegawa, Mitsuhiko, [939] Hasegawa, Y., [914] Hashemi, Masoud Reza, [1124] Hashida, Mitsuru, [60] Hassanien, Aboul Ella, [1074] Hata, Yutaka, [286, 641, 672] Hattori, Yuya, [838] Hauke, S., [389] Hawley, William A., [686] Hayashi, Yoichi, [240] Hayaska, Satoru, [1062] Haydon, Daniel, [188] Hayenga, Heather N., [1054] Hazen, Stanley L., [703] He, Langchong, [69] He, Lifeng, [370] He, Li-Hua, [724] He, Renjie, [271] He, Sailing, [203] He, Wenxing, [1151] He, Xining, [1056] He, Ying, [854] Heang, Ping Chan, [507] Hedström, Anders, [148] Heider, D., [389] Heinrichs, Volker, [24] Helguera, Maŕıa, [344] Helguera, Maria, [312, 328, 737] Helvie, Mark A., [457, 464, 940, 507] Helwig, Bryan G., [715] Hemayed, E., [479] Hemayed, Elsayed E., [953] Hemmateenejad, Bahram, [634, 71, 81] Hemon, Denis, [762] Heng, Pheng-Ann, [241] Hennig, Carsten, [608] 26 Genetic algorithms in medicine Henriques, J., [1057] Heris, S. Mostapha Kalami, [759] Heritage, Trevor W., [141] Hernandez-Garcia, Luis, [1160] Herrera, Manuel, [697] Herrmann, W. M., [944, 961] Hervas-Martinez, Cesar, [1153] Herzmann, Grit, [404] Hess, A. J., [253] Hessler, Gerhard, [63] Hickson, I. D., [747] Higa, Masaru, [766] Higami, T., [630] Higuchi, Tetsuya, [667, 998] Hijazi, Hussein, [856] Hiley, M. J., [745] Hill, A., [226] Hillis, David M., [163] Hiltner, Jens, [912] Hiltner, J., [256] Hinds, R. Michael, [438] Hines, Evor L., [801] Hinson, Arthur, [1034] Hirako, Kenichi, [445] Ho, Christine, [819] Hoehn, Gerard, [703] Hoey, Tim, [648] Hoffmeister, Jeffrey W., [239, 243, 247, 262, 533] Hoh, Jeong-Kyu, [1117] Holder, Mark T., [163] Holland, Brett, [29] Holls, William, [555] Holmes, E. C., [955] Holmes, John H., [576, 929] Honeyman, Marco, [135] Hong, Mei-zhu, [744] Hong, Seunghong, [493, 500] Hong, Wenxue, [1055] Hong, Xiao-Dan, [833] Honørio, Nildimar Alves,[684] Hopfinger, A. J., [994] Horan, M. A., [577, 595, 966] Horan, Michael A., [950] Horgan, Richard P., [752] Horita, Katsuhei, [445] Horner, Steven L., [555] Hornero, Roberto, [1115] Hossain, M. A., [1110] Hosseini, Z. S., [970, 983] Hosseinifard, Behshad, [1068] Hoth, J. Jason, [729] Hou, Q., [1096] Hou, Tingjun, [1009] Hou, Weidong, [1036] Hricak, H., [237] Hsu, Ching-Chi, [663, 849] Hsu, Hsiang-Ming, [1162] Hsu, Wei-Yen, [887, 898, 899] Hu, Benqiong, [177] Hu, Dingyu, [62] Hu, Qingmao, [430] Hu, Wen-Chen, [195, 1048, 390] Hu, Y., [813] Hu, Yiyang, [891] Hua, Jing, [307] Huang, C. L., [524] Huang, Chung-Hsien, [300] Huang, Cunrui, [855] Huang, Guanghui, [99] Huang, Haiyan, [819] Huang, He, [1122] Huang, Jau-Hua, [300] Huang, Liling, [834] Huang, N., [852] Huang, Shuying, [358] Huang, Wenhua, [430] Huang, Wen-qi, [744] Huang, Wenqing, [873] Huang, Xiaosheng, [379] Huang, Xiaowu, [763] Huang, Xudong, [177] Huang, Yan-xin, [173] Huang, Yueh-Min, [1035] Huang, Zhiwei, [757] Hubley, Robert M., [165] Hughes, Ian, [31] Hugh-Jones, Martin E., [681, 711] Humphrey, Jay D., [1054] Hung, Chih-Cheng, [733] Hunt, David L., [31] Huo, Liqin, [1056] Husbands, Phil, [721] Hussain, Zakaria, [1128] Hust, Michael, [728] Hutz, Janna, [789] Hwa, Er Meng, [581] Hynynen, Kullervo, [267] Ibáñez, L., [191] Idicula, Sumam Mary, [830] Igel, Christian, [605, 352] Ikenberg, Hans, [387] Ikezoe, J., [999] Ikuta, Kunihiko, [896] Ilancheran, A., [757] Ileanǎ, Ioan, [613] Ilhan, Ilhan, [179] Iliescu, Daciana D., [801] Il’ina, E. N., [712] Im, Chang-Hwan, [895] Imberty, Anne, [847] Impedovo, Donato, [791] Inaba, Takeshi, [370] Ingole, V. T., [371] Inman, Brant A., [784] Intraligi, Marco, [644] Isa, Nor Ashidi Mat, [1128] Isacke, Clare M., [851] Ishida, Toshimasa, [766] Ishigaki, Takeo, [445] Ishigaki, T., [264, 485] Ito, Hiroshi, [766] Ito, Masahiro, [896] Itoh, H., [449] Itoh, S., [264, 485] Ivy, Percy S., [57] Iwata, Masaya, [667, 998] Authors 27 Iyengar, S. Sitharama, [384] Iyengar, S. S., [359] Izadiyan, Parisa, [772] Izquierdo, Joaqúın, [697] Jackowiak, Paulina, [907] Jackson, M. I., [745] Jacq, Jean-José, [1022, 501, 227] Jadhav, Swapnil D., [76] Jafari, Amir Homayoun, [790] Jafari, Seyed Ali, [883] Jafarpour, Mehrnaz, [98] Jaffar, M. Arfan, [413] Jahandideh, Mina, [883] Jahandideh, Sepideh, [883] Jahromi, P. Eftekhar, [45] Jain, Sunil K., [713] Jakobsson, Stefan, [148] Jalali-Heravi, M., [45, 54] Jalalvand, Ali R., [905] Jalbert, Llewellyn, [773] Janc, K., [1073] Jang, Younggun, [493, 500] Janikow, Cezary Z., [559] Jansen, A., [389] Janssen, M. A., [949] Jantschi, Lorentz, [102] Javid, Samad, [1078] Jefferson, M. F., [595, 966] Jefferson, Miles F., [950] Jen, Lim Chong, [581] Jenkins, Jeremy L., [789] Jenssen, Havard, [55] Jewajinda, Yutana, [431] Jha, Tarun, [96, 877] Ji, Bingbing, [778] Ji, Fei, [726] Ji, Jun, [1152] Jia, Chunguang, [505] Jia, Jianping, [800] Jia, Yingmin, [819] Jian, Hualing, [128] Jiang, Chang-Bin, [835] Jiang, Ching-Fen, [251] Jiang, Gang, [177] Jiang, Jack J., [1040] Jiang, Jingying, [651] Jiang, Mingfeng, [671, 746, 873] Jiang, Ouyang Guotai, [143] Jiang, Qiuyue, [169] Jiang, Shanshan, [873] Jiang, Tianzi, [248, 272, 275, 277] Jiang, Wei, [769] Jiang, Xiaoqian, [180] Jiang, Zhibin, [1129] Jiao, Lijing, [874] Jin, Albert Yongwon, [129] Jin, Bo, [1152] Jin, Qi, [885] Jin, Yaochu, [890] Jitaru, Maria, [613] Johansson, C. B., [296] Johnson, Donald E., [1116] Johnson, Mark S., [30] Johnston, Victor, [1167] Jokerst, Nan M., [426] Jolivot, R., [799] Jones, Gareth, [139] Jones, Jennifer T., [24] Jones, Matthew D., [1099] Joshi, Anjali, [371] Jourdan, Laetitia, [623] Joyce, Karen E., [1062] Joyner, Timothy Andrew, [711] Jr, V. Pilla, [538] Ju, Quan, [339] Ju, Wenbin, [876] Judson, Olivia P., [188] Juhola, Martti, [591, 489, 1084, 982, 991, 1000] Jung, Byungjo, [1039] Jung, Hsuan, [734] Jung, Young-Jin, [895] Jurs, Peter C., [134] Kaabouch, Naima, [368, 195, 1048, 390] Kabuka, Mansur R., [498] Kachelriess, Marc, [412] Kacprzynski, G. J., [253] Kadah, Yasser M., [313, 329] Kaderali, Lars, [886] Kagadis, G. C., [268] Kai, Toshihiro, [794] Kaiser-Bonasso, Christine, [455] Kajihara, N., [998] Kajitani, I., [998] Kajitani, Isamu, [667] Kakar, Manish, [365] Kalantari, Masoud, [802] Kalderstam, Jonas, [858] Kalganova, Tatiana, [622] Kallarakkal, Thomas George, [758] Kalra, Naveen, [425, 433] Kaltsatis, P., [979] Kam, A., [521] Kamano, T., [975] Kamarulzaman, Hamzah, [403] Kan, Jichang, [197] Kang, Chu Chun, [722] Kang, Yujung, [380] Kanniainen, Olli, [693] Kao, Ceng-Yan, [130] Kao, Cheng-Yan, [1023, 119] Kao, Jui-Hung, [147] Kao, Ming-Hung, [366] Karajeh, Huda, [1041] Karami, Ghodrat, [1078] Karbakhsh, R., [48] Kareem, Sameem Abdul,[758] Karimi, Koohyar, [691] Karimi, Reza, [348] Karkavitsas, George, [298] Karnan, M., [1042] Karouzakis, K., [612, 614] Karthikeyan, Kayathri, [844] Kashanian, Mehdi, [193] Kasibotla, Agasthya V., [84] 28 Genetic algorithms in medicine Kasprzak, Wojciech, [742] Katkova, Ekaterina V., [95] Katti, Seturam B., [49] Kawamura, T., [630] Kaya, Mehmet, [214] Ke, J. Y., [951] Kehtamavaz, Nasser, [627] Keijzer, Maarten, [647] Kell, Douglas B., [207, 653, 752] Kemsley, E. Kate, [795] Kendell, D., [1101] Kenny, Bob, [270] Kenny, Louise C., [653, 752] Kent, Alexander R., [843] Kentala, Erna L., [591, 991] Kermani, Bahram Ghaffarzadeh, [1087] Kewley, Robert H., [23] Keymeulen, Didier, [998] Khabbaz, Kamal R., [859] Khader, Ahamad Tajudin, [403] Khadivi, Pejman, [1124] Khajeh, Mostafa, [875] Khalaf, Reema Abu, [33] Khalil, Ahmad S., [660] Khaloozadeh, Hamid, [759] Khan, Mahvish, [56] Khan, Riaz A., [106] Khan, Saif, [56] Khandelwal, Niranjan, [425, 433] Khani, Hadi, [767] Khatchikian, C., [1101] Khayati, Rasoul, [419] Khazaee, Ali, [1052] Kherlopian, Armen R., [783] Khiani, K. J., [481] Khomitch, Vitali, [638] Khoo, V. S., [1092] Khoobehi, Bahram, [359, 384] Khoshneviszadeh, Mehdi, [71] Khotanlou, Hassan, [407] Kido, Choichiro, [445] Kikuchi, T., [999] Kim, B. Y., [570] Kim, Byung-Chun, [770] Kim, Chae-Yong, [902] Kim, Daejeong, [895] Kim, Dong Gyu, [902] Kim, H. C., [706] Kim, Jung-Hoon, [895] Kim, Soo Hyung, [399] Kim, Young-Hoon, [902] Kimura, Toru, [794] King, M. A., [827] Kinghorn, B., [158] Kini, P., [556] Kinjo, Tomohiro, [109] Kinoshita, Kengo, [175] Kircher, T., [389] Kirkman, E., [966] Kiryati, Nahum, [301] Kishi, S., [914] Kishore, N. N., [369] Kitamura, Mitsuru, [109] Kitney, Richard I., [1075] Klein, T. A., [706] Klema, Jiri, [211] Kléma, Jǐŕı, [1038] Klinkenberg, Brian, [710] Kloppel, B., [930] Knaup, Michael, [412] Knoll, Peter, [270, 285] Kobashi, Syoji, [286, 641, 672] Kobayashi, Maiko, [109] Kobayashi, Yasuhiko, [838] Koçer, Sabri, [144] Kodali, Shyam P., [369] Koh, Chan G., [589] Koh, Chang Seop, [302, 354] Köhler, Bert-Uwe, [608] Khn, Horst, [270] Kohzadi, M., [114] Koistinen, Hannu, [732] Kokol, Peter, [1094] Kokol, P., [583, 383, 219, 972, 1010] Kokot, Serge, [837] Koljonen, Janne, [693, 548, 549] Komatsu, Hideyuki, [109] Kondakova, Olga A., [35] Kondo, Katsuya, [286, 641, 672] Kong, Nan, [892] Kong, Xiangzhen, [768] Koppen, M., [234] Koralewski, Hans-Eberhard, [564, 1019] Korber, Bette, [818] Koriska, Karl, [270] Korkin, Dmitry, [22] Korner, A., [978] Korngreen, Alon, [685, 822] Kos, Bor, [775] Koseki, Yuji, [109] Koski, Kristine G., [812, 840] Kosugi, Y., [200, 441] Kosugi, Yukio, [529] Kotcheff, A. C. W., [216] Kotcheff, A. C., [491] Koutcher, J. A., [237] Kovačič, Miha, [657] Kovecses, Jozsef, [802] Kozmann, G., [1146, 637] Kramer, Kirsten Elisabeth, [650] Krantz, Lena, [654] Krestyannikov, Evgeny, [327] Kreusch, J., [965, 525] Krieg, Rene C., [387] Krishna, Murali C., [367] Krishnan, Shekhar, [42] Krogh-Madsen, Trine, [783] Krohn, Jorgen, [780] Krol, A., [737] Krol, Andrzej, [312, 328, 344] Krol, Marcin, [42] Krone, Joerg, [220] Kruggel, F., [446] Kubalik, Jiri, [211] Kubaĺık, Jǐŕı, [1038] Authors 29 Kubinyi, Hugo, [133] Kudaka, M., [518] Kühl, Christofer, [269] Kuhne, Ronald, [85] Kuiken, Carla, [818] Kuklinski, Walter S., [910, 437] Kula, M. R., [1024] Kulandaivelu, Umasankar, [75] Kulkov, Val, [59] Kulubekova, Saule, [882] Kumar, A. Senthil, [640, 664] Kumar, M. Aswath, [779] Kumar, Pradeep, [106] Kumar, Praveen, [750, 409, 77] Kumar, Sumit, [78] Kumar, Sunil, [707] Kumar, Vinod, [425, 433] Kumaravel, N., [1026, 1139] Kumari, V. Vijaya, [308] Kuncheva, Ludmila I., [560] Kundu, M. K., [332] Kuntz, Irwin D., [28] Kunwar, Rakesh Singh, [393] Kupinski, M. A., [531] Kupinski, Matthew A., [206, 478] Kupinski, M., [460] Kurnaz, Mehmet Nadir, [276] Kuroda, K., [1082] Kurosaka, M., [672] Kurtzman, Aaron L., [24] Kurzydlowski, Krzysztof J., [832] Kutics, A., [447] Kutics, Andrea, [451, 467] Kutov, Danil C., [95] Kuznetsov, Yuryi V., [35] Kwok, James T., [318] Kwok, Leung Lam, [507] Kwon, Jangwoo, [493, 500] Kwon, Kihwan, [380] Kyani, Anahita, [55] Labelle, Hubert, [871] Lago, M. A., [1071] Lahanas, M., [612, 614, 1140, 1002] Lahiri, Tapobrata, [170] Lahsasna, Adel, [1113] Lahtela-Kakkonen, Maija, [732] Lai, Feipei, [147] Lai, Peggy S., [867] Lai, Yan-Hua, [836] Lainscsek, C., [782] La Rocca, Renato, [278] Lam, Andy Yan-Yu, [147] Lam, Hong Yoong, [403] Lam, Kwok L., [457] Lam, W., [244] Lamarque, D., [799] Lambrou, Antonis, [1051] Lammi, S., [1000] Lan, Yihua, [733] Lanconelli, N., [249, 604] Land, W. H., [979] Land, Walker H., [205, 242, 263] Landini, Luigi, [410] Landrin-Schweitzer, Yann, [288] Lane, R., [1134] Langenberger, Thierry, [509] Langer, Mark, [1134] Lanzeni, Stefano, [678] Larrañaga, Pedro, [945] Larra naga, Pedro, [957] Larrañaga, Pedro, [960] Larson, Scott R., [702] Laskaris, N., [221] Lau, Audrey O. T., [792] Lau, Tze Kin, [252] Laughton, C. A., [747] Laurienti, Paul J., [1062] Laurikkala, Jorma, [591, 257, 952, 489, 1084, 982, 991, 1000] Lavine, B. K., [813] Law, Tsui-Ying, [241] Lazar, Cosmin, [90] Lazaro-Ponthus, Delphine, [363, 374] Lazorchak, Jim, [174] Leach, Andrew R., [139] Leader, Joseph K., [399] Leal, Rogerio P., [1076] Lederman, Dror, [717, 1102, 397, 399, 841] Lee, Andrew, [1123] Lee, Dah-Jye, [692] Lee, D., [782] Lee, Dong-Yup, [777] Lee, E. K., [992] Lee, Eunsil, [493] Lee, HeowPueh, [664] Lee, Howard, [848] Lee, Jiann-Der, [300, 458, 470] Lee, Joon, [735, 859] Lee, June-Goo, [1111, 416] Lee, Jungsul, [380] Lee, Man-Ling, [19] Lee, Mei-Ling Tin, [1117] Lee, Ming-Yuan, [829] Lee, O., [1134] Lee, P. V., [495] Lee, Peter V., [513] Lee, Sangjean, [500] Lee, Sangmin, [493] Lee, T., [1137] Lee, Tong, [252] Lee, Yongbum, [264, 292, 485, 512] Leendert, R. van, [567] Leeson, Mark S., [801] LeFevre, J., [931] Legoupil, Samuel, [363, 374] Legrand, Pierrick, [687, 375] Lehmann, Thomas M., [235] Lehndert, R. van, [566] Lei, Beilei, [40] Lei, Jie, [1044, 1045, 1050] Leirs, Herwig, [695] Lenski, Richard E., [161] Leon, Lisa R., [715] Lerch, R., [561] Leren, T. P., [1027] 30 Genetic algorithms in medicine Leren, Troud P., [157] Letellier, C., [782] Leung, Kwong Sak, [238, 244] Levenson, Richard M., [638] Levin, Michael, [924] Levine, Rebecca S., [686, 700] Levy-Drummer, Rachel S., [316] Levy-Vehel, Jacques, [687] Lewin, Jonathan S., [291] Lewis, Paul O., [163] Lewis, Paul S., [1165, 229] Leyman, A. Rahim, [581] Lhotská, Lenka, [1038] Li, Bailiang, [889] Li, C., [325] Li, George Q., [1072] Li, Guo, [835] Li, Jia, [62] Li, Jiazhong, [89] Li, Jing, [1055, 835] Li, Jingya, [62] Li, Jingyi Jessica, [819] Li, Junbo, [1030, 1031, 980] Li, Jung-Chike, [842] Li, Jupeng, [324] Li, King C. P., [854] Li, King, [703] Li, Kong M., [1072] Li, Leling, [942] Li, Lihua, [841] Li, Li, [769, 864] Li, Lin, [800] Li, Ming-Xi, [716] Li, Na, [855] Li, Ningshan, [893] Li, Pengfei, [69, 889] Li, Qiao, [906] Li, Qingli, [196] Li, Shan, [889] Li, Shao-Xin, [1065] Li, Shiyong, [373] Li, Shutao, [318] Li, Temei, [617] Li, Wei, [769] Li, W., [353] Li, Wuxiong, [648] Li, Xia, [769] Li, Xiangchen, [180] Li, Xiangyan, [768] Li, Xiaodong, [248] Li, Xiaomei, [341] Li, Xue-Mei, [716] Li, Xue-Wang, [716] Li, Yangmei, [1030, 1031] Li, Yan, [44, 835] Li, Yanlian, [62] Li, Yongjie, [633, 1044, 1045, 1050] Li, Yupeng, [1123] Li, Zhan-Chao, [836] Li, Zhi-Qiang, [835] Lian, Baofeng, [769] Liang, Chunlin, [1126] Liang, David, [83] Liang, Hualou, [1090, 486] Liang, Xuwei, [307] Liao, Mingzhi, [769] Liaw, C. Y., [589] Lieberman, Jeffrey A., [57] Liengsawangwong, R., [325] Likotjannasis, S. D., [607, 618] Lim, Gino J., [1123] Lima, W. C. de, [948] Limbert, Georges, [754] Lin, Cui, [307] Lin, Feng-Seng, [147] Lin, Jeng-Wei, [147] Lin, Jinn, [663, 894] Lin, Ming-Cheng, [807] Lin, Qihua, [785] Lin, Shih-Wei, [415] Lin, Xiaoling, [855] Lin, Xi-Zhang, [436] Lin, X., [326] Lin, Yu-Da, [1125, 178] Lin, Zhiyue, [1090] Linares, P., [503] Lindholm-Sethson, Britta, [548, 549] Lindon, John C., [765] Lineaweaver, Sean, [645] Ling, Steve S. H., [1058] Ling, Xuefeng B., [1152] Ling, Xuefeng Bruce, [648] Linkens, D. A., [590] Linkens, Derek A., [932] Lipinski, P., [1073] Litt, Brian, [1034] Little, R. A., [966] Liu, Boqiang, [341] Liu, Chang, [864] Liu, Chunyang, [889] Liu, Dan, [169] Liu, Dongxiang, [128] Liu, Feng, [746] Liu, Gui-xia, [173] Liu, Hong, [733] Liu, Huanxiang, [40] Liu, Huaying, [1122] Liu, Jane Jijun, [648] Liu, Jia-kuang, [514, 540] Liu, Jianghong, [800] Liu, Jingao, [196] Liu, JiZhong, [42] Liu, Kun-Hong, [876] Liu, Li-Chang, [300] Liu, Li, [739, 1056] Liu, Linda Y., [1152] Liu, Ning-Han, [1162] Liu, Qiao-Dan, [835] Liu, Qingzhong, [177] Liu, Renyu, [83] Liu, Shih-Ting, [147] Liu, Song-Hao, [1065] Liu, Taotao, [763] Liu, Wei, [1123, 841] Liu, X. Y., [171] Liu, Xiaohui, [616] Authors 31 Liu, Xue-Jiao, [716] Liu, Xun, [893] Liu, Y., [171] Liu, Yong, [450, 959, 1012] Liu, Yuan, [800] Liu, Zhi-Gang, [835] Liu, Zhi-Ming, [1065] Liu, Zhiyue, [486] Liu, Zhongguo, [341] Livdahl, T., [1101] Ljubic, Ivana, [788] Lo, Joseph Y., [205, 242, 263] Lo, Justin Y., [426] Locke, A. G., [862] Lockwood, Larry, [26, 27] Lodhi, Mazhar U., [82] Loke, Pei Yi, [749] Lončarić, Sven, [439] Longini, Ira M. Jr, [861] Lonning, Per E., [1063] Lopes, H. S., [996, 538] Lopes, Heitor S., [620, 948] Lopez, Heitor Silvério, [149] Lopez-Andujar, R., [1071] Lou, Tanqi, [893] Louchet, Jean, [363, 374] Lounibos, L. Philip, [686] Loureiro, Joseph, [789] Lovy, Linda S., [717] Low, Jeffrey J. H., [757] Lu, Hengyun, [1149] Lu, Shiyong, [307] Lu, Weixue, [505] Lu, Xinxin, [863] Lucas, S. B., [577, 966, 565] Lucas, Sam B., [950] Luitgards-Moura, José Francisco, [679, 684] Lukhnova, Larissa, [711] Lundgren, Steinar, [1063] Luo, Mei-Juan, [833] Luo, X., [559] Lupsor, Monica, [753] Lursinsap, Chidchanok, [903] Lustrek, Mitja, [740, 805, 821] Lutton, Evelyne, [288, 687] Lutton, Évelyne, [363, 374, 1061] Lutton, Evelyne, [406] Lv, Linsheng, [893] Lv, Yingli, [769] Lyell, Deirdre J., [1152] Ma, Huijuan, [893] Ma, Lanping, [62] Ma, Li Zhuang, [891] Määttä, Juha A. E., [732] Mace, Michael, [904] Maciunas, Robert, [626] MacKenzie, Sasho J., [826] Madadkar-Sobhani, Armin, [41] Madadlou, Ashkan, [815] Maddalena, D. J., [127] Madhavan, Radhika, [866] Madheswaran, Muthusamy, [1120] Madhusudan, S., [747] Madi, Arwa M., [58] Madihally, Sundar, [86] Maeda, Chika, [641] Maggini, Valentina, [166] Magill, Lukas C., [46] Magill, Peter J., [900] Mahan, S. L., [665] Mahanand, B. S., [779] Mahendar, Porika, [75] Mahfouf, M., [590] Mahiou, Ramdane, [333, 349] Mahmoodi, M. Mohsen, [45] Mahmoodian, Hamid, [793] Mai, Hai-Qiang, [1065] Mainardi, Luca, [1161] Majdi-Nasab, Nariman, [17] Maji, Pradipta, [332] Majumder, M. A. A., [1110] Majumder, P. P., [580] Mak, Sunny, [710] Makrogiannis, Sokratis, [335] Malcic, I., [219] Malhotra, Harish K., [1099] Malik, Sarfraz Ahmed, [393] Mallet, Nicolas, [900] Man, K. F., [951] Mancinelli, Livia, [787] Mandal, Abhyuday, [366] Mandava, Venkat R., [225, 204] Manetta, S., [510] Manetti, Cesare, [787] Mani, Haresh, [414] Maniadakis, M., [575] Mani-Varnosfaderani, A., [45, 54] Mann, D., [595] Mantzaris, Dimitrios, [723] Manuck, Stephen B., [57] Manzano, Mark, [742] Manzoni, Pietro, [869] Mao, Chi-Wu, [436] Mao, C., [852] Mao, Qian-guo, [744] Marchesi, Bruno, [149] Marchetti, Mauro, [1161] Marchi, Alessandra, [878] Março, Paulo Henrique, [1059, 1060] Marcos, J. Victor, [1115] Marcus, Emil, [125] Marder, Stephen R., [57] Marinelli, Martina, [410] Marjoram, Paul, [734] Marks, Lawrence B., [694] Maroulis, D., [213] Marq, Benoit M., [508] Marquez, Guillermo, [627] Marrakchi-Kacem, Linda, [421] Marten, Frank, [145] Martens, J. M., [949] Martinez, Francisco J., [869] Martinez-Martinez, F., [1071] Martinez-Perez, I., [456] Martin-Guerrero, J. D., [1071] 32 Genetic algorithms in medicine Martini, Anna, [314] Martins, Maria, [1077] Martis, R. J., [908] Mart́ınez-Campos, Carmen, [636] Mart́ınez-Meyer, Enrique, [636] Marvin, N., [1004] Marzani, F., [799] Masotti, Andrea, [787] Massa, Andrea, [246, 314] Massad, E., [1085] Masters, G., [922] Masters, Timothy D., [242, 263] Mastronardi, G., [294] Mastronardi, Guiseppe, [378] Mata, la, Manuel d, [1153] Matecha, J., [194] Matero, Sanni, [732] Matrajt, Laura, [861] Matsopoulos, George K., [254, 268, 969, 1088] Matsubara, Tomoko, [445] Matsui, Kazuhiro, [529] Matsui, K., [200, 441] Matsumoto, Hiroyuki, [939] Matter, Hans, [63] Matteucci, Matteo, [1161] Mattsson, Johanna M., [732] Maulik, Ujjwal, [1046, 846, 886] Maus, Bärbel, [776] Maxwell, R. J., [456] Mayaud, Louis, [867] Mazaki, Yusaku, [896] McAllister, Gregory, [789] Mccall, J. A. W., [527] McCall, John, [635] McCallum, R. W., [486] McCallum, Richard W., [1090] McCowan, Lesley M., [752] McCurdy, B., [1106] McDonnell, John R., [925] McDowell, J. J., [857, 882] McInerney, Tim, [273] McIntosh, Chris, [306] McKee, Dan, [263] McLaren, CVhristine E., [691] McNay, D., [461] McNyset, Kristina M., [681] McTavish, Thomas, [1159] McWeeney, Shannon, [811] Mechref, Y., [813] Medina, Veronica, [260] Medina, V., [284] Meesad, P., [261] Mehdipour, Ahmadreza, [74] Mehrabian, Mohadeseh, [55] Mehrshad, N., [1104] Mehta, Akul Y., [79] Meng, Fan-Liang, [724] Meng, Tao, [62] Menigot, Sebastien, [427] Merican, Amir Feisal Merican Aljunid, [758] Merino, Maria J., [414] Mertik, M., [383] Mesgari, Mohammad Saad, [424] Meskens, N., [666] Messina, Enza, [678] Messing, E. M., [993, 1014] Metallo, Christian M., [797] Metzger, A., [1093] Metzler, Volker, [220] Meuli, Reto, [509] Meunier, Jean, [259] Meunier, J., [532] Meyer, Claudia M., [228] Meyer zu Bexten, E., [256] Mezura, Efren, [806] Micera, Silvestro, [1105] Michelena, M. J., [957] Michielssen, Eric, [1160, 461] Middleton, L. T., [562, 563] Miften, Moyed, [694] Mignotte, Max, [259] Mignotte, M., [532] Mihara, Kiyoshi, [60] Miklavcic, Damijan, [775] Miliani, L., [223] Milickovic, N., [612, 614] Mills, J. A., [919, 934, 954, 971] Min, David I., [995] Minowa, Yohsuke, [794] Minster, J. B., [922] Mirakhorli, Shima, [767] Miranda, Dinis Reis, [1001] Miranda, Pedro Cavaleiro, [901] Miranda, P., [520] Miranda-Saavedra, Diego, [810] Miri, Ramin, [71, 74, 81] Mirjankar, N., [813] Mirza, Sikander M., [317, 334, 334, 338, 340, 350, 396] Mirzaei, Siroos, [270] Mirzaei, S., [285] Mishra, A., [305] Mishra, Hrishikesh, [170] Mishra, Vijay, [713] Misra, Krishna, [170] Mitamura, Yoshinori, [766] Mitchell, Melanie, [315] Mitra, Pabitra, [1028] Mitra, Suman K., [1138] Mitra, Sushmita, [1028, 240] Miyake, Yoichi, [376] Miyata, Yujiro, [185] Miyokawa, T., [976] Mo, Yulong, [1036] Mobli, Hossien, [815] Mochizuki, T., [999] Mofrad, Mohammad R. Kaazempur, [660] Mofrad, Mohammed R. Kaazempur, [348] Moghadam, Z. Razaghi Kashan, [814] Moghimi, S., [828] Mohamed, S., [966] Mohammed, M. Z., [747] Mohan, S., [989] Mohri, K., [88] Authors 33 Moini, Majid, [879] Molaei, Damoon, [424] Moldoveanu, F., [494] Molinari, Filippo, [825] Molinari, F., [908] Monakov, Mikhail Yu, [35] Mondal, Chanchal, [877] Monserrat, C., [1071] Montalvo, Idel, [697] Monteiro de Barros, Fábio Saito, [679, 684] Montilla, G., [503] Montilla, Guillermo, [223, 224] Mookiah, M. R. K., [908] Moon, Woo Kyung, [415] Mooney, Michael, [811] Moore, Jason H., [164, 1080] Moradi, Mohammad Hassan, [1068] Moraga, C., [256] Morais, J., [1057] Morales Cruzado, Beatriz, [1069] Morbiwala, Tasnim A., [872] Moreno, L., [210, 1037] Moreno, Rui, [1001] Morgan, Alexander A., [1152] Morgan, K., [577] Morgera, Andrea, [1147] Morita, Koji, [109] Morrill, S., [1134] Morrison, Clayton T., [205] Mortazavi, S. S., [100, 113] Mosher, John C., [1165, 229] Mosier, Philip D., [107] Moskowitz, Myron, [455] Motokawa, Wataru, [1025] Mouravliansky, Nicolaos A., [254, 268, 969, 1088] Mubarak, Mohammad S., [33, 47] Muge, Fernando, [588] Muhammad, Majidat A.,[818] Mukamel, S., [1158] Mukherjee, Anirban, [755] Mukhopadhyay, Anirban, [846, 886] Muldoon, Matthew F., [57] Mun, S. K., [476] Munshi, Prabhat, [369] Muraca, Maurizio, [787] Murakami, Kazuhito, [370] Murakami, M., [998] Murase, K., [999] Murugan, S., [709] Murugesan, R., [367] Musolino, Nicholas, [97] Myers, Jenny, [653] Myers, Timothy G., [968] Nagayama, I., [518] Nagel, R., [492] Nagle, H. Troy, [1087] Nagpal, Isha, [67] Naguib, Ibrahim A., [66] Najarian, Siamak, [879] Nakaguchi, Toshiya, [376] Nakamura, Ikuo, [472] Nakano, Manami, [670] Nakao, Zensho, [466, 472, 483, 487, 490, 497, 543] Nakazawa, Yoshinori, [636] n, [?] na, Gabriel Ma}ga06aGManana Nandi, Dipankar, [904] Nandi, Sisir, [51] Nandy, Rajesh, [404] Narayana, Ponnada A., [271] Narayanan, M. N., [565] Narayanasamy, P., [187] Narimani, Hojat, [897] Narita, M., [938, 941] Nasab, Nariman Majdi, [14] Nassar, Diaa Eldin, [16] Näıt-Ali, Amine, [361] Naushahi, Mohammad, [904] Nayebzadeh, M., [970, 983] Nazareth, Daryl P., [1099] Nazem-Bokaee, Hadi, [881] Ndesendo, Valence M. K., [106] Neely, Brian J., [86] Neerinckx, Simon B., [695] Neff, Bryan D., [167] Neglia, Danilo, [410] Nellen, F., [1024] Nelson, J. Stuart, [1039] Nelson, Sarah J., [773] Nemeth, S. C., [290] Nerurkar, Ashutosh, [851] Neto, M. Augusta, [1076] Neumann, Avidan U., [316] Neumann, Martin, [270] Nevado-Holgado, Alejo J., [145, 900] Nevo, Uri, [809] Ng, E. Y. K., [385] Ng, Joseph, [757] Ng, L., [191] Ngan, P. S., [244] Ngo, L. H., [862] Nguyen, Hung T., [1058] Ni, Guangzheng, [302] Ni, Yan-fei, [726] Ni, Yongnian, [837] Nian, Wen, [482] Niccolai, M. J., [202] Nicholis, Thomas E., [287] Nickolay, B., [234] Niederberger, Craig, [933] Nielsen, Carsten Uhd, [50] Nigsch, Florian, [789] Nikiforidis, G. C., [268] Nikita, Konstantina S., [969, 1088] Nilsen-Hamilton, Marit, [756] Nishikawa, D., [998] Nishikawa, R. M., [492] Nishimura, Ikuya, [766] Nishimura, Y., [976] Nissanov, Jonathan, [301] Nithiyanandam, N., [1139] Niu, Dao-Li, [835] Noorizadeh, Hadi, [92, 100, 897, 112, 113, 114, 115] Noorizadeh, Mehrab, [897] 34 Genetic algorithms in medicine Noorizadeh, Mehrad, [100, 112, 113, 114] Nordal, Inger, [157] Nordal, I., [1027] Nordling, Torbjörn E. M., [693, 548, 549] Norouzi, Parviz, [37] North, Robyn A., [752] Novelline, Robert, [416] Novic, Marjana, [116] Novikov, Fedor N., [59] Nowack, W. J., [202] Nowe, Ann, [90] Nowshirava Rahatabad, Fereidoun, [790] Nowzari-Dalini, A., [814] Nugroho, Hermawan, [774] Nunes, Jean-Claude, [311, 364] Nunes, Rodolfo Acatauassu, [434] Nürnberg, H. G., [1021, 568] Nyongesa, H. Okola, [932] Nyström, Josefina, [548, 549] Ocak, Hasan, [1130] Ochoa, Edward M., [239, 243, 247, 262, 265, 533] O’Connor, Patrick M., [968] Oechtering, Peter, [480] Oferkin, Igor V., [95] Offman, Marc N., [42] Ogirala, Mythili, [15, 16] Oguz, Kaya, [435] Oh, Chang Wan, [902] Ohkubo, Masaki, [292] Ohlsson, Mattias, [858] Ohno, Yasuo, [794] Ohno-Machado, L., [582, 1008] Ohta, Hiroyuki, [175] Okamura, T., [474] Okazaki, K., [482] Okunieff, P. G., [993, 1014] Okunieff, P., [585] Oliveira, Dário A. B., [377] Oliveira, Dario A. B., [382] Ölmez, Tamer, [1033, 276] Olmez, T., [956, 516] Ölmez, T., [541] Olmi, R., [510] Olsen, Dag Rune, [365] Ong, Kok Meng, [642] Ono, Atsushi, [794] Onorati, Francesco, [1161] Onori, Manuela, [787] Onuki, T., [976] Orglmeister, Reinhold, [608] Ortega, Francis A., [783] Osin, Peter, [851] Osman, Muhammad Khusairi, [1128] Osowski, Stanislaw, [760] Osuna-Enciso, Valent́ın, [428] Ota, Motonori, [175] Ouh-Young, Ming, [119] Ouhyoung, Ming, [130] Owen, F., [595] Ozaki, Masao, [1025] Ozdemir, Muhsin, [26, 27] Ozyurt, Ibrahim Burak, [796] Pace, Fabio, [644] Padilla Castañeda, M. 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D., [925] Parthiban, Latha, [550] Parvaneh, Saman, [824] Pascual-Leone, Alvaro, [901] Pasqualoto, Kerly Fernanda M., [39] Passaretti, Sandro, [644] Passaro, Alessandro, [166] Pastorelli, Stefano, [1100] Pastorino, Matteo, [246, 314] Patel, Apoorva, [159] Patel, H. C., [994] Patel, Naina, [42] Patel, P. M., [747] Patel, Paresh K., [64] Patete, Paolo, [878] Patten, Philip A., [24] Pattichis, C. S., [562, 563] Pattichis, Constantinos S., [935] Authors 35 Patton, Robert M., [698] Patton, Ronald J., [778] Paul, Jochen, [566, 567] Paull, Kenneth D., [968] Paulson, Rolf, [368, 195, 1048] Pavlidis, Stelios P., [761] Payandeh, Shahram, [617] Payer, Hannes, [331] Payne, Annette M., [761] Pazilov, Yerlan, [711] Pazos, Alejandro, [462] Péan, Vincent, [687, 375] Pechlivanis, Ioannis, [352] Peck, Charles C., [556, 228] Pedersen, Lee G., [942] Pedrycz, Witold, [1145] Pei, Xiaohua, [893] Peirce, Shayn M., [1054] Peña-Reyes, Carlos Andrés, [579, 587, 598, 609, 629, 1006, 1015] Pendleton, Neil, [950] Pendleton, N., [577, 595, 966] Peng, Jinglin, [318] Peng, Lingxi, [1126] Peng, Luying, [864] Peng, Shih Chi, [722] Peng, Sihua, [648] Peng, Wen, [319] Peng, Yidong, [892] Peng, Zhengwei, [111] Penttinen, Jorma, [982] Perez, Juan Manuel Sanchez, [727] Perez, Serge, [847] Perez-Aguilar, Jose Manuel, [83] Perez-Castillo, Yunierkis, [90] Persson, Mikael, [148] Peters, Ashton, [323] Peters, Tim K., [564, 1019] Peterson, A. Townsend, [628, 636, 1097, 684, 1098, 699] Peterson, Andrew T., [695] Petrick, Nicholas, [457, 464, 940, 507] Petrovski, Andrei, [635] Petrovski, A., [527] Pfeiffer, Dirk U., [738] Pfotenhauer, M., [567] Pfurtscheller, G., [913] Pham, Tuan D., [362] Phimoltares, Suphakant, [903] Piazzolla, Alessandro, [378] Picaza, J. M., [957] Piccione, Francesco, [1161] Pickens, III, David R., [225, 204] Pickering-Brown, S., [595] Pickett, Stephen D., [31] Picton, P. D., [536] Picu, Dorin, [566, 567] Pilla, Jr V., [996] Pillay, Viness, [106] Pinto, Peter A., [414] Pirlo, Giuseppe, [791] Piscaglia, Patrick, [508] Pitcher, Trevor E., [167] Pitiot, Alain, [266] Pizzi, Nicolino J., [1145] Playfer, Jeremy R., [339] Plishker, William, [345, 360] Podbregar, Matej, [657] Podforelec, V., [972] Podgorelec, Vili, [1094] Podgorelec, V., [583, 219, 1010] Poh, Chueh Loo, [1075] Pohida, Thomas, [414] Pohlmann, A., [578] Poizner, H., [782] Poli, Riccardo, [282, 916, 1081, 471, 523, 231] Polifeme, C., [592] Pollock, Bruce G., [57] Polo, Stephanie, [742] Pont, M. J., [946] Poon, Josiah, [874] Poon, Simon, [874] Popa, Maria, [613] Poppi, Ronei J., [597] Poppl, S. J., [965, 525] Porro, Gabriele Bianchi, [644] Porto, V. W., [947, 981, 988] Poshtan, Javad, [1109] Positano, Vincenzo, [410] Poso, Antti, [732] Potok, Thomas E., [698] Potrebko, P., [1106] Poupon, Anne, [764] Pour-Abdollah, Syamak, [535] Pourabdollah-Nezhad, Siamak, [233, 255] Pourbasheer, Eslam, [37] Pourhossein, Alireza, [41] Pournajafi, K., [100] Power, Maxine, [1047] Prabhakar, Yenamandra S., [49] Prather, Jonathan Charles, [236] Praveen, Vandana, [56] Preece, Steve J., [280] Preema, N., [683] Pregenzer, M., [913] Prieto, Victor, [627] Priftis, Konstantinos, [1161] Priori, S., [510] Proutski, V., [955] Pu, Yuepu, [803] Pueh, Lee Heow, [640] Pulido, Juan Antonio Gomez, [727] Puranen, J. Santeri, [30] Putignani, Lorenza, [787] Putra, Devi, [778] Pyka, M., [389] Pyykkö, Ilmari V., [591, 991] Qadri, Muhammad A. J., [1163, 1164] Qian, Guipeng, [319] Qian, Z., [353] Qiao, Yuchen, [800] Qin, Jianxin, [855] Qiu, Qingjun, [651] Qu, Xiuli, [892] Quesneville, Hadi, [160] 36 Genetic algorithms in medicine Quintana, M. I., [282] Qureshi, Shahzad Ahmad, [317, 334, 334, 338, 340, 350, 396] Rabani, Yuval, [184] Rabinovich, Yuri, [184] Rad, Farshid Rafiee, [233, 255] Rad, Gholam Ali Rezaei,[193] Rad, Michael von, [909] Radhakrishnan, S., [709] Radhika, Tippani, [75] Radonjic, Marijana, [795] Rafferty, Kimberly, [328, 344] Rafferty, K., [737] Rafiee, Rad, [535] Rafiee, Shahin, [815] Rahmati, Mohammad, [535] Raicu, Daniela, [408] Raj, Isha, [67] Rajagopalan, Cadathur, [906] Rajaguru, Harikumar, [146] Rajapakse, Jagath C., [528] Rajpoot, Nasir M., [396] Ram, Ramesh, [172] Raman, B., [290] Ramanujam, Nirmala, [426] Ramchandra, T. V., [751] Ramos, Vitorino, [588] Ramsey, C. R., [665] Rangel, Naykiavick, [223, 224] Rangoussi, Maria, [298] Raoofi, F., [100] Rapin, Nicolas, [50] Rapoport, Benjamin I., [866] Rathbun, Thomas F., [239, 243, 245, 247, 265] Rathbun, Thomas P., [262, 533] Rautenbach, R., [1020] Raveendran, P., [642] Ray, Rajasri, [751] Razjouyan, Javad, [790] Razmovski-Naumovski, Valentina, [1072] Razon, Benjamin, [822] Razuc, Mariela F., [870] Razzaghi-Asl, Nima, [74] Rødningen, Olaug K., [157] Rebelo, Irene, [1127] Reddy, A. Srinivas, [707] Redfern, M. S., [962] Reeves, C. R., [934] Reichert, Erin D., [742] Reinstein, L. E., [499] Rejto, Paul A., [923, 937] Ren, Bin, [833] Repsilber, Dirk, [740, 805, 821] Resch, Robert, [331] Resenstengel, John E., [265] Restrepo, Diego, [1159] Reynolds, E. C., [862] Reynolds, Mary G., [700] Rezaei, Asghar, [1078] Riahi, Siavash, [37] Riane, F., [661] Ricciotti, Gabriella, [787] Rice, William R., [162] Rich, S. S., [1142] Richardson, Mark P., [145] Rigby, Alan C., [942] Rigotti, Gino, [878] Rijckaert, Marcel, [27] Rijckaert, M., [586] Rimm, David L., [638] Ripolles, Oscar, [901] Ritchie, Marylyn D., [164] Riyahi-Alam, Nader, [445] Roach, Jared C., [165] Roberts, C. B., [662] Roberts, Claire T., [752] Roberts, J., [118] Roberts, M., [283, 289] Roberts, S., [479] Robinson, M. P., [798] Robinson, Robert L. Jr, [86] Rocchisani, Jean-Marie, [363, 374] Rocha, T., [1057] Rodningen, O. K., [1027] Rodriguez, L., [503] Rodriguez, Miguel A. Vega, [727] Roemer, M. J., [253] Rogers, Jack T., [177] Rogers, R. L., [461] Rogers, Steven K., [239, 243, 245, 247, 262, 533] Rogers, Steven, [265] Roig, José V., [697] Roland, B., [661] Romano, A., [494] Romanov, Alexey N., [35] Romero, Eduardo, [309] Romero, Leoncio A., [806] Rong, Ying-Ci, [833] Rongguo, Yan, [320] Roohafza, Hamidreza, [880] Rosani, Andrea, [314] Rosati, Samanta, [825] Roseiro, Luis M., [1076] Rosenberg, R. S., [156] Rosenman, M. A., [683] Rosenstengel, John E., [239, 243, 247] Rosentengel, John E., [262, 533] Ross, Anton, [728] Ross, T., [965, 525] Rost, Ursula, [480] Rostami, Reza, [1068] Rouet, Jean-Michel, [1022, 501] Routen, T., [453] Roux, Christian, [1022, 501, 223, 227] Rovithakis, G., [575] Rowat, P., [782] Rowbottom, C. G., [1092] Rowe, Jonathan E., [1004] Rubens, D. J., [993, 1014] Ruberto, Cecilia Di, [1147] Rudy, George, [135] Rueda, L. M., [706] Rueda, Leopoldo M., [1098] Ruffini, Giulio, [901] Ruotsalainen, Ulla, [327] Authors 37 Ruperez, M. J., [1071] Ruspini, E. H., [209] Sa, S. D., [938] Sa, S., [941] Saadatzi, Mohammad Nasser, [1109] Saadatzi, Mohammad Sadegh, [1109] Saba, L., [908] Sabet, Razieh, [81] Sabet, R., [48] Sabin, Andrew T., [845] Sacchettini, James C., [109] Sadanandam, Abbagani, [75] Sadeghi, Masoumeh, [880] Saeedi, Nafise Erfanian, [748] Saghaei, Lotfollah, [81] Saghaie, Lotfollah, [41] Saghaie, L., [103] Sagi, Elad, [872] Saha, Achintya, [96] Saha, Sriparna, [420] Saha, Vaskar, [42] Sahin, Kader, [36, 73] Sahiner, Berkman, [457, 464, 940, 507] Saidman, Elbio, [870] Sajjadifar, Sami, [115] Sakamoto, Hiroshi, [109] Sakamoto, Shinchi, [600] Sakanashi, H., [998] Sale, Mark E., [57, 848] Sale, Mark, [105] Sali, Rasoul, [880] Salmelin, Riitta, [1157, 936, 1086] Samarra, Miguel C., [1076] Sampson, Jessica, [688] Sandham, W. A., [274] Sangermano, F., [1101] Santamaŕıa, José, [304, 321, 386, 395, 421, 432] Santibáñez-Koref, Ivan, [190] Santiso, Erik E., [97] Santos, Antonino, [462] Santos, Cristina, [1077] Santvoort, J. P. C. van, [1143] Saracoglu, Ridvan, [1053] Sarafraz-Yazdi, Ali, [875] Sarai, Akinori, [43] Saraswathi, Saras, [756] Sarbadhikari, S. N., [1138] Saripinar, Emin, [36, 73, 101] Sarkar, Anita, [847] Sarkar, Susanta K., [335] Sarkhosh, Maryam, [52] Sarrafzadegan, Nizal, [880] Sasa, Yukako, [60] Sasaki, Satoshi, [708] Sase, M., [200, 441] Sasikala, M., [1026] Satake, H., [975] Sathya, Shree Rajesh K.,[731] Saven, Jeffery G., [83] Savinova, T. A., [712] Sawall, Stefan, [412] Scachetti Pereira, Ricardo, [628] Scalerandi, M., [494] Schaffer, J. David, [680] Schell, M. C., [585, 1135, 1136, 484, 993] Scher, Howard I., [57] Scherg, Michael, [150] Scherg, M., [1003] Schettino, L., [782] Scheubert, Lena, [740, 805, 821] Schierz, Amanda C., [1148] Schiex, Thomas, [186] Schiffman, Susan S., [1087] Schirmer, R. Heiner, [601] Schizas, C. 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V., [920, 558] Seburyano, G., [979] Sedykh, Aleksandr Y., [619] Seitz, Jr., Kerry A., [408] Seki, H., [449] Sekiya, Masaru, [292] Sekkal, Mansouria, [1107] Selber, K., [1024] Selinger, Douglas W., [789] Senger, Ryan S., [881] Sengupta, Sanghamitra, [755] Sengupta, Soumi, [87] Sepulveda, Francisco, [1108] Sergi, Pier Nicola, [1105] Settouti, Nesma, [1107] Seyhan, N., [673] Shabani, Ali Mohammad Haji, [52] Shafiei, Mohammad, [104] Shah, Nilay D., [784] Shah, Priyanka, [78] Shah, S., [747] Shah, Vijay, [414] Shahabipour, Sara, [74] Shahin, Rand, [80, 93] Shahlaei, Mohsen, [41] Shahlaei, M., [103] Shaik, Osman S., [715] Shalom, David H., [316] Shamsi, Mousa, [1118] Shamsudin, Norashikin, [774] Shane, M. J., [649] Shankar, Prakhya Laxmi Jaya, [75] 38 Genetic algorithms in medicine Shao, Hongwei, [854] Shapiro, Bruce A., [742] Shattuck, David W., [327] Shavandi, Hassan, [880] Sheehan, N., [1156] Shehadehh, Mayyada, [61] Shekhar, Raj, [345, 360] Shelhamer, Mark, [1029] Shen, Chia-Ping, [147] Shen, Gary X., [337] Shen, Jing Jin, [802] Shen, Jingkang, [62] Shen, Lansun, [232] Shen, Xizhong, [763] Shen, Yi, [373] Shenton, Martha, [273] Sherer, Eric A., [57, 105] Sherman, Christopher J., [923] Shete, Deepak, [371] Shi, Haiying, [1056] Shi, Jing, [892] Shi, Leming M., [968] Shi, Tongwei, [889] Shi, Weifang, [888] Shi, Yinghuan, [429] Shi, Yuhui, [515] Shibanuma, Nao, [641] Shibanuma, N., [672] Shin, Chulkyu, [493, 500] Shionoya, Akira, [939] Shionoya, Akitaka, [896] Shirvany, Yazdan, [148] Shityakov, Sergey, [108] Shively, J. 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A., [569] Silvern, David a., [572] Silvern, D., [992] Silvoni, Stefano, [1161] Simon, Dan, [974] Simpson, Mark R., [680] Sinauridze, Elena I., [35] Sinclair, A., [184] Sing, Chong Chiet, [640] Singh, Harsimrat, [801] Singh, Nitya, [170] Singh, Ranjit, [409] Singh, Rinki, [49] Singh, Yogendra, [110] Sipper, Moshe, [579, 587, 598, 1006, 1015] Sirisha, Kalam, [75] Siroic, Robert, [760] Sitter, Beathe, [1063] Siwek, Krzysztof, [760] Skinner, Cameron D., [812, 840] Skov, Thomas, [905] Small, Gary W., [973] Smith, Stephen L., [689, 339] Snowdon, G. M., [127] Sobhan-Ardakani, S., [100] Sobhan Ardakani, S., [113] Soh, Chit Siang, [642] Soh, Zu, [838] Solit, David B., [57] Soliz, P., [290] Solomonidis, S. 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W., [1097, 674] Swieszkowski, Wojciech, [832] Swift, Stephen M., [761] Swift, Stephen, [616, 336] Szathmary, Eors, [721] Sze, Daniel Man-Yuen, [874] Tabrizian, Kaveh, [104] Tadikonda, Satish K., [465] Tadikonda, Satish Kumar, [448, 230] Taga, Ichiro, [630, 646, 670] Taha, Mutasem O., [32, 33, 34, 47, 61, 80, 93] Taheri, Javid, [1066] Taherinia, D., [45] Tai, David, [38] Takagi, Hideyuki, [600] Takashibu, Midori, [466, 487, 490] Talbi, El-Ghazali, [623] Tal-Botzer, Ronen, [316] Talebi, M., [828] Talhami, Habib, [443] Talley, S., [643] Taminau, Jonatan, [90] Tamura, Shinichi, [472] Tamura, S., [482] Tan, Chao, [719] Tan, Chin-Tuan, [872] Tan, Jen Hong, [385] Tan, Jun, [397, 399] Tan, Ou, [505] Tang, Chuan Yi, [722] Tang, Jijun, [182] Tang, K. 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Patent
01 Nov 2013
Abstract: A dynamically reconfigurable framework manages processing applications in order to meet time-varying constraints to select an optimal hardware architecture. The optimal architecture satisfies time-varying constraints including for example, supplied power, required performance, accuracy levels, available bandwidth, and quality of output such as image reconstruction. The process of determining an optimal solution is defined in terms of multi-objective optimization using Pareto-optimal realizations.

10 citations


Journal ArticleDOI
TL;DR: A novel multiobjective wordlength optimization strategy developed through FPGA-based implementation of a representative computationally intensive image processing application: medical image registration is presented and may be adapted to a wide range of signal processing applications.
Abstract: In real-time signal processing, a single application often has multiple computationally intensive kernels that can benefit from acceleration using custom or reconfigurable hardware platforms, such as field-programmable gate arrays (FPGAs). For adaptive utilization of resources at run time, FPGAs with capabilities for dynamic reconfiguration are emerging. In this context, it is useful for designers to derive sets of efficient configurations that trade off application performance with fabric resources. Such sets can be maintained at run time so that the best available design tradeoff is used. Finding a single, optimized configuration is difficult, and generating a family of optimized configurations suitable for different run-time scenarios is even more challenging. We present a novel multiobjective wordlength optimization strategy developed through FPGA-based implementation of a representative computationally intensive image processing application: medical image registration. Tradeoffs between FPGA resources and implementation accuracy are explored, and Pareto-optimized wordlength configurations are systematically identified. We also compare search methods for finding Pareto-optimized design configurations and demonstrate the applicability of search based on evolutionary techniques for identifying superior multiobjective tradeoff curves. We demonstrate feasibility of this approach in the context of FPGA-based medical image registration; however, it may be adapted to a wide range of signal processing applications.

7 citations


Proceedings ArticleDOI
01 Apr 2009
TL;DR: It is shown that a single core on 412MHz XC5VLX330T FPGA can evaluate a rigid transformation of a 3D image with 16 million voxels in 35ms, over 108 times faster than a multi-threaded implementation running on a 2.5GHz Intel Quad-Core Xeon platform.
Abstract: This paper proposes techniques for accelerating a software based image registration algorithm for 3D medical images targeting a reconfigurable hardware platform. Various methods, including dedicated fixed point arithmetic, error model based bit width analysis, architecture exploration and application-specific memory modules, are applied to address issues from the software algorithm and to maximize the performance of FPGA technology. Based on the reconfigurability of FPGA devices, the system can be extended to swap modules optimized for different parameters, and to adopt more advanced registration algorithms. We show that a single core on 412MHz XC5VLX330T FPGA can evaluate a rigid transformation of a 3D image with 16 million voxels in 35ms. With 30 cores on an FPGA, it is over 108 times faster than a multi-threaded implementation running on a 2.5GHz Intel Quad-Core Xeon platform.

4 citations


Cites background from "Multiobjective Optimization of FPGA..."

  • ...In 2008, a multi-objective optimization framework for precision and resource trade off is proposed [6]....

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References
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Journal ArticleDOI
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Abstract: Multi-objective evolutionary algorithms (MOEAs) that use non-dominated sorting and sharing have been criticized mainly for: (1) their O(MN/sup 3/) computational complexity (where M is the number of objectives and N is the population size); (2) their non-elitism approach; and (3) the need to specify a sharing parameter. In this paper, we suggest a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties. Specifically, a fast non-dominated sorting approach with O(MN/sup 2/) computational complexity is presented. Also, a selection operator is presented that creates a mating pool by combining the parent and offspring populations and selecting the best N solutions (with respect to fitness and spread). Simulation results on difficult test problems show that NSGA-II is able, for most problems, to find a much better spread of solutions and better convergence near the true Pareto-optimal front compared to the Pareto-archived evolution strategy and the strength-Pareto evolutionary algorithm - two other elitist MOEAs that pay special attention to creating a diverse Pareto-optimal front. Moreover, we modify the definition of dominance in order to solve constrained multi-objective problems efficiently. Simulation results of the constrained NSGA-II on a number of test problems, including a five-objective, seven-constraint nonlinear problem, are compared with another constrained multi-objective optimizer, and the much better performance of NSGA-II is observed.

30,928 citations


Journal ArticleDOI
Eckart Zitzler1, Lothar Thiele1Institutions (1)
TL;DR: The proof-of-principle results obtained on two artificial problems as well as a larger problem, the synthesis of a digital hardware-software multiprocessor system, suggest that SPEA can be very effective in sampling from along the entire Pareto-optimal front and distributing the generated solutions over the tradeoff surface.
Abstract: Evolutionary algorithms (EAs) are often well-suited for optimization problems involving several, often conflicting objectives. Since 1985, various evolutionary approaches to multiobjective optimization have been developed that are capable of searching for multiple solutions concurrently in a single run. However, the few comparative studies of different methods presented up to now remain mostly qualitative and are often restricted to a few approaches. In this paper, four multiobjective EAs are compared quantitatively where an extended 0/1 knapsack problem is taken as a basis. Furthermore, we introduce a new evolutionary approach to multicriteria optimization, the strength Pareto EA (SPEA), that combines several features of previous multiobjective EAs in a unique manner. It is characterized by (a) storing nondominated solutions externally in a second, continuously updated population, (b) evaluating an individual's fitness dependent on the number of external nondominated points that dominate it, (c) preserving population diversity using the Pareto dominance relationship, and (d) incorporating a clustering procedure in order to reduce the nondominated set without destroying its characteristics. The proof-of-principle results obtained on two artificial problems as well as a larger problem, the synthesis of a digital hardware-software multiprocessor system, suggest that SPEA can be very effective in sampling from along the entire Pareto-optimal front and distributing the generated solutions over the tradeoff surface. Moreover, SPEA clearly outperforms the other four multiobjective EAs on the 0/1 knapsack problem.

6,717 citations


"Multiobjective Optimization of FPGA..." refers result in this paper

  • ...These performance measures are similar to those reported in [24] and are described below....

    [...]


Journal ArticleDOI
Frederik Maes1, A Collignon1, Dirk Vandermeulen1, Guy Marchal1  +1 moreInstitutions (1)
TL;DR: The results demonstrate that subvoxel accuracy with respect to the stereotactic reference solution can be achieved completely automatically and without any prior segmentation, feature extraction, or other preprocessing steps which makes this method very well suited for clinical applications.
Abstract: A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence or information redundancy between the image intensities of corresponding voxels in both images, which is assumed to be maximal if the images are geometrically aligned. Maximization of MI is a very general and powerful criterion, because no assumptions are made regarding the nature of this dependence and no limiting constraints are imposed on the image content of the modalities involved. The accuracy of the MI criterion is validated for rigid body registration of computed tomography (CT), magnetic resonance (MR), and photon emission tomography (PET) images by comparison with the stereotactic registration solution, while robustness is evaluated with respect to implementation issues, such as interpolation and optimization, and image content, including partial overlap and image degradation. Our results demonstrate that subvoxel accuracy with respect to the stereotactic reference solution can be achieved completely automatically and without any prior segmentation, feature extraction, or other preprocessing steps which makes this method very well suited for clinical applications.

4,580 citations


"Multiobjective Optimization of FPGA..." refers background in this paper

  • ...MI-based image registration has been shown to be robust and effective in multimodality image registration [15]....

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  • ...[15] has been shown to provide smooth changes in the histogram values with small changes in transformation....

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Book
01 Jan 1999

1,635 citations


"Multiobjective Optimization of FPGA..." refers methods in this paper

  • ...An optimum wordlength configuration can be identified by analytically solving the quantization error equation as described in [4-8]....

    [...]

  • ...Earlier approaches to optimizing wordlengths used analytical approaches for range and error estimation [4-8]....

    [...]


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