Showing papers by "General Electric published in 2011"

A Survey of Condition Monitoring and Protection Methods for Medium-Voltage Induction Motors

Abstract: Medium-voltage (MV) induction motors are widely used in the industry and are essential to industrial processes. The breakdown of these MV motors not only leads to high repair expenses but also causes extraordinary financial losses due to unexpected downtime. To provide reliable condition monitoring and protection for MV motors, this paper presents a comprehensive survey of the existing condition monitoring and protection methods in the following five areas: thermal protection and temperature estimation, stator insulation monitoring and fault detection, bearing fault detection, broken rotor bar/end-ring detection, and air gap eccentricity detection. For each category, the related features of MV motors are discussed; the effectiveness of the existing methods are discussed in terms of their robustness, accuracy, and implementation complexity. Recommendations for the future research in these areas are also presented.

A High Power Density Single-Phase PWM Rectifier With Active Ripple Energy Storage

Abstract: It is well known that single-phase pulse width modulation rectifiers have second-order harmonic currents and corresponding ripple voltages on the dc bus. The low-frequency harmonic current is normally filtered using a bulk capacitor in the bus, which results in low power density. However, pursuing high power density in converter design is a very important goal in the aerospace applications. This paper studies methods for reducing the energy storage capacitor for single-phase rectifiers. The minimum ripple energy storage requirement is derived independently of a specific topology. Based on the minimum ripple energy requirement, the feasibility of the active capacitor's reduction schemes is verified. Then, we propose a bidirectional buck-boost converter as the ripple energy storage circuit, which can effectively reduce the energy storage capacitance. The analysis and design are validated by simulation and experimental results.

Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules

Abstract: We propose a method for comparing density forecasts that is based on weighted versions of the continuous ranked probability score. The weighting emphasizes regions of interest, such as the tails or the center of a variable’s range, while retaining propriety, as opposed to a recently developed weighted likelihood ratio test, which can be hedged. Threshold- and quantile-based decompositions of the continuous ranked probability score can be illustrated graphically and provide insight into the strengths and deficiencies of a forecasting method. We illustrate the use of the test and graphical tools in case studies on the Bank of England’s density forecasts of quarterly inflation rates in the United Kingdom, and probabilistic predictions of wind resources in the Pacific Northwest.

Combinatorial and High-Throughput Screening of Materials Libraries: Review of State of the Art

Abstract: Rational materials design based on prior knowledge is attractive because it promises to avoid time-consuming synthesis and testing of numerous materials candidates. However with the increase of complexity of materials, the scientific ability for the rational materials design becomes progressively limited. As a result of this complexity, combinatorial and high-throughput (CHT) experimentation in materials science has been recognized as a new scientific approach to generate new knowledge. This review demonstrates the broad applicability of CHT experimentation technologies in discovery and optimization of new materials. We discuss general principles of CHT materials screening, followed by the detailed discussion of high-throughput materials characterization approaches, advances in data analysis/mining, and new materials developments facilitated by CHT experimentation. We critically analyze results of materials development in the areas most impacted by the CHT approaches, such as catalysis, electronic and fun...

Battery Technologies for Large-Scale Stationary Energy Storage

Abstract: In recent years, with the deployment of renewable energy sources, advances in electrified transportation, and development in smart grids, the markets for large-scale stationary energy storage have grown rapidly. Electrochemical energy storage methods are strong candidate solutions due to their high energy density, flexibility, and scalability. This review provides an overview of mature and emerging technologies for secondary and redox flow batteries. New developments in the chemistry of secondary and flow batteries as well as regenerative fuel cells are also considered. Advantages and disadvantages of current and prospective electrochemical energy storage options are discussed. The most promising technologies in the short term are high-temperature sodium batteries with β″-alumina electrolyte, lithium-ion batteries, and flow batteries. Regenerative fuel cells and lithium metal batteries with high energy density require further research to become practical.

Materials and transducers toward selective wireless gas sensing.

Abstract: Wireless sensors are devices in which sensing electronic transducers are spatially and galvanically separated from their associated readout/display components. The main benefits of wireless sensors, as compared to traditional tethered sensors, include the non-obtrusive nature of their installations, higher nodal densities, and lower installation costs without the need for extensive wiring.1–3 These attractive features of wireless sensors facilitate their development toward measurements of a wide range of physical, chemical, and biological parameters of interest. Examples of available wireless sensors include devices for sensing of pH, pressure, and temperature in medical, pharmaceutical, animal health, livestock condition, automotive, and other applications.4–7 Some implementations of wireless gas sensors can be already found in monitoring of analyte gases (e.g. carbon dioxide, water vapor, oxygen, combustibles) in relatively interference-free industrial and indoor environments.8,9 However, unobtrusive wireless gas sensors are urgently needed for many more diverse applications ranging from wearable sensors at the workplace, urban environment, and battlefield, to monitoring of containers with toxic industrial chemicals while in transit, to medical monitoring of hospitalized and in-house patients, to detection of food freshness in individual packages, and to distributed networked sensors over large areas (also known as wireless sensor networks, WSNs). Unfortunately, in these and numerous other practical applications, the available wireless gas sensors fall short of meeting emerging measurement needs in complex environments. In particular, existing wireless gas sensors cannot perform highly selective gas detection in the presence of high levels of interferences and cannot quantitate several components in gas mixtures. 1.1. Diversity Of Monitoring Needs Of Volatiles The monitoring of numerous gases of environmental, industrial, and homeland security concern is needed over the broad range of their regulated exposure concentrations. Figure 1 illustrates the relationships between several regulated exposure levels spanning several orders of magnitude of gas concentrations. Typical examples of concentrations of regulated exposure are presented in Table 110–14 for three groups of toxic volatiles such as volatile organic compounds (VOCs), toxic industrial chemicals (TICs), and chemical warfare agents (CWAs). These examples demonstrate the need for gas sensing capabilities with broad measurement dynamic ranges to cover 2 – 4 orders of magnitude in gas concentrations. Figure 1 Examples of regulated vapor-exposure limits established by different organizations: GPL: General Population Limit, established by USACHPPM – U.S. Army Center for Health Promotion and Preventative Medicine; PEL: Permissible Exposure Limit, established ... Table 1 Examples of regulated concentration levels (in ppm by volume) from three representative classes of toxic gases: VOCs, TICs, and CWAs.10–14 Additional needs for detection of volatiles originate from medical diagnostics, food safety, process monitoring, and other areas.15–17 In those applications, the types and levels of detected volatiles can provide the needed information for further control actions.

Dynamic nuclear polarization polarizer for sterile use intent

Abstract: A novel polarizer based on the dissolution-dynamic nuclear polarization (DNP) method has been designed, built and tested. The polarizer differs from those previously described by being designed with sterile use intent and being compatible with clinical use. The main features are: (1) an integral, disposable fluid path containing all pharmaceuticals constituting a sterile barrier, (2) a closed-cycle cryogenic system designed to eliminate consumption of liquid cryogens and (3) multi-sample polarization to increase throughput. The fluid path consists of a vial with the agent to be polarized, a pair of concentric inlet and outlet tubes connected to a syringe with dissolution medium and a receiver, respectively. The fluid path can operate at up to 400 K and 2.0 MPa and generates volumes as high as 100 mL. An inline filter removes the amount of electron paramagnetic agent in the final product by more than 100-fold in the case of [1-13C]pyruvate. The system uses a sorption pump in conjunction with a conventional cryocooler. The system operates through cycles of pumping to low temperature and regeneration of the sorption pump. The magnet accommodates four samples at the same time. A temperature of less than 1 K was achieved for 68 h (no sample heat loads) with a liquid helium volume of 2.4 L. The regeneration of the liquid helium could be achieved in less than 10 h, and the transition to cold (< 1.2 K) was achieved in less than 90 min. A solid state polarization of 36 ± 4% for [1-13C]pyruvic acid was obtained with only 10 mW of microwave power. The loading of a sample adds less than 50 J of heat to the helium bath by introducing the sample over 15 min. The heat load imposed on the helium bath during dissolution was less than 70 J. The measured liquid state polarization was 18 ± 2%. Copyright © 2011 John Wiley & Sons, Ltd.

10 kV, 120 A SiC half H-bridge power MOSFET modules suitable for high frequency, medium voltage applications

Abstract: The majority carrier domain of power semiconductor devices has been extended to 10 kV with the advent of SiC MOSFETs and Schottky diodes. The devices exhibit excellent static and dynamic properties with encouraging preliminary reliability. Twenty-four MOSFETs and twelve Schottky diodes have been assembled in a 10 kV half H-bridge power module to increase the current handling capability to 120 A per switch without compromising the die-level characteristics. For the first time, a custom designed system (13.8 kV to 465/√3 V solid state power substation) has been successfully demonstrated with these state of the art SiC modules up to 855 kVA operation and 97% efficiency. Soft-switching at 20 kHz, the SiC enabled SSPS represents a 70% reduction in weight and 50% reduction in size when compared to a 60 Hz conventional, analog transformer.

Fault-tolerant permanent magnet machines: a review

Abstract: Synchronous permanent magnet (PM) machines have been gaining a lot of interest over the years. This is due to their several advantages including high power density, high efficiency and high reliability. One of the key concerns about PM machines especially in safety-critical applications (such as the more-electric aircraft) has been the issue of fault-tolerance since the machine cannot be de-excited. A lot of work has been done both on the machine side as well as the power converter side (including power converter configuration and remedial control strategies). This study will provide a thorough review and summary of what has been covered in literature up-to-date. The study will highlight the tradeoffs (including weight, cost and reliability) involved in the various proposed methods and strategies with more emphasis on the machine side. The methods discussed in this study include active control methods form converter side, memory motors, doubly-salient and flux-switching machines, use of auxiliary windings, mechanical flux-weakening methods, use of shunts and shields, thermal protection and transverse flux machines. The study will also include some comments about where the research in this area is heading in the future.

System, charging device, and method of charging a power storage device

Abstract: A system for charging a plurality of power storage devices includes a first charging device and at least one other charging device coupled to the first charging device to form a network. The first charging device includes a processor programmed to determine whether said first charging device possesses a network token, and if so, to determine a first charging parameter and a first priority associated with said first charging device, a second charging parameter and a second priority associated with said second charging device, and to determine a second amount of current to be at least one of received from the electrical supply or supplied to the first power storage device, based on the determined first and second charging parameters and first and second priority.

Method and system for cropping a 3-dimensional medical dataset

Abstract: A method and gesture-based control system for manipulating a 3-dimensional medical dataset include translating a body part, detecting the translation of the body part with a camera system. The method and system include translating a crop plane in the 3-dimensional medical dataset based on the translating the body part. The method and system include cropping the 3-dimensional medical dataset at the location of the crop plane after translating the crop plane and displaying the cropped 3-dimensional medical dataset using volume rendering.

Nanomedicine, Nanotechnology in medicine

Abstract: Nanomedicine is a relatively new field of science and technology. It looks sometimes ill defined and interpretations of that term may vary, especially between Europe and the United States. By interacting with biological molecules, therefore at nanoscale, nanotechnology opens up a vast field of research and application. Interactions between artificial molecular assemblies or nanodevices and biomolecules can be understood both in the extracellular medium and inside the human cells. Operating at nanoscale allow to exploit physical properties different from those observed at microscale such as the volume/surface ratio. The investigated diagnostic applications can be considered for in vitro as well as for in vivo diagnosis. In vitro, the synthesized particles and manipulation or detection devices allow for the recognition, capture, and concentration of biomolecules. In vivo, the synthetic molecular assemblies are mainly designed as a contrast agent for imaging. A second area exhibiting a strong development is the "nanodrugs" where nanoparticles are designed for targeted drug delivery. The use of such carriers improves the drug biodistribution, targeting active molecules to diseased tissues while protecting healthy tissue. A third area of application is regenerative medicine where nanotechnology allows developing biocompatible materials which support growth of cells used in cell therapy. The application of nanotechnology to medicine raises new issues because of new uses they allow, for instance: Is the power of these new diagnostics manageable by the medical profession? What means treating a patient without any clinical signs? Nanomedicine can contribute to the development of a personalized medicine both for diagnosis and therapy. There exists in many countries existing regulatory frameworks addressing the basic rules of safety and effectiveness of nanotechnology based medicine, whether molecular assemblies or medical devices. But there is a need to clarify or to modify these regulations which mobilize many experts. France is a country where the medical development of nanotechnology is significant, like Germany, the United Kingdom or Spain, as regards the European Union. There is an active scientific community and industrial partners of all sizes, even if the technology transfer to industry is not as effective as in North America.

Appearance-based person reidentification in camera networks: problem overview and current approaches

Abstract: Recent advances in visual tracking methods allow following a given object or individual in presence of significant clutter or partial occlusions in a single or a set of overlapping camera views. The question of when person detections in different views or at different time instants can be linked to the same individual is of fundamental importance to the video analysis in large-scale network of cameras. This is the person reidentification problem. The paper focuses on algorithms that use the overall appearance of an individual as opposed to passive biometrics such as face and gait. Methods that effectively address the challenges associated with changes in illumination, pose, and clothing appearance variation are discussed. More specifically, the development of a set of models that capture the overall appearance of an individual and can effectively be used for information retrieval are reviewed. Some of them provide a holistic description of a person, and some others require an intermediate step where specific body parts need to be identified. Some are designed to extract appearance features over time, and some others can operate reliably also on single images. The paper discusses algorithms for speeding up the computation of signatures. In particular it describes very fast procedures for computing co-occurrence matrices by leveraging a generalization of the integral representation of images. The algorithms are deployed and tested in a camera network comprising of three cameras with non-overlapping field of views, where a multi-camera multi-target tracker links the tracks in different cameras by reidentifying the same people appearing in different views.

Common-Mode Circulating Current Control of Paralleled Interleaved Three-Phase Two-Level Voltage-Source Converters With Discontinuous Space-Vector Modulation

Abstract: This paper presents a control method to limit the common-mode (CM) circulating current between paralleled three-phase two-level voltage-source converters (VSCs) with discontinuous space-vector pulsewidth modulation (DPWM) and interleaved switching cycles. This CM circulating current can be separated into two separate components based on their frequency; the high-frequency component, close to the switching frequency, can be effectively limited by means of passive components; the low-frequency component, close to the fundamental frequency, embodies the jumping CM circulating current observed in parallel VSCs. This is the main reason why it is usually recommended not to implement discontinuous and interleaving PWM together. The origin of this low-frequency circulating current is analyzed in detail, and based on this, a method to eliminate its presence is proposed by impeding the simultaneous use of different zero vectors between the converters. This control method only requires six additional switching actions per line cycle, presenting a minimum impact on the converter thermal design. The analysis and the feasibility of the control method are verified by simulation and experimental results.

Automatic fall detection based on Doppler radar motion signature

Abstract: Falling is a common health problem for elderly. It is reported that more than one third of adults 65 and older fall each year in the United States. To address the problem, we are currently developing a Doppler radar-based fall detection system. Doppler radar sensors provide an inexpensive way to recognize human activity. In this paper, we employed mel-frequency cepstral coefficients (MFCC) to represent the Doppler signatures of various human activities such as walking, bending down, falling, etc. Then we used two different classifiers, SVM and kNN, to automatically detect falls based on the extracted MFCC features. We obtained encouraging classification results on a pilot dataset that contained 109 falls and 341 non-fall human activities.

Systems, methods, and apparatus for identifying invalid nodes within a mesh network

Abstract: Systems (100), methods (300), and apparatus for identifying invalid nodes within a mesh network (105) are provided. A routing table (104) may be maintained by a utility meter (120). The routing table (140) may include information associated with one or more devices in communication with the utility meter via a mesh network. A change in the routing table may be identified by the utility meter (120), and an alert message associated with the identified change may be generated by the utility meter (120). The generated alert may then be output by the utility meter for communication to a central controller (110) configured to process the alert message to identify an invalid node within the mesh network.

Utility powered communications gateway

Abstract: Described herein are embodiments of methods, systems and devices of providing a communications gateway between one or more first networks and a second network. In accordance with one aspect, a method is provided comprising receiving, by a first device, information communicated from one or more first networks, wherein the first device is a low power device; and transmitting, by a second device, at least part of the information over a second network, wherein the second device is a high power device and wherein the first device and the second device receive power from a wired communications system.

Entangled decision forests and their application for semantic segmentation of CT images

Abstract: This work addresses the challenging problem of simultaneously segmenting multiple anatomical structures in highly varied CT scans. We propose the entangled decision forest (EDF) as a new discriminative classifier which augments the state of the art decision forest, resulting in higher prediction accuracy and shortened decision time. Our main contribution is two-fold. First, we propose entangling the binary tests applied at each tree node in the forest, such that the test result can depend on the result of tests applied earlier in the same tree and at image points offset from the voxel to be classified. This is demonstrated to improve accuracy and capture long-range semantic context. Second, during training, we propose injecting randomness in a guided way, in which node feature types and parameters are randomly drawn from a learned (non-uniform) distribution. This further improves classification accuracy. We assess our probabilistic anatomy segmentation technique using a labeled database of CT image volumes of 250 different patients from various scan protocols and scanner vendors. In each volume, 12 anatomical structures have been manually segmented. The database comprises highly varied body shapes and sizes, a wide array of pathologies, scan resolutions, and diverse contrast agents. Quantitative comparisons with state of the art algorithms demonstrate both superior test accuracy and computational efficiency.

Improving bone formation in a rat femur segmental defect by controlling bone morphogenetic protein-2 release.

Abstract: Nonunion is a common complication in open fractures and other severe bone injuries. Recombinant human bone morphogenetic protein-2 (rhBMP-2) delivered on a collagen sponge enhances healing of fractures. However, the burst release of rhBMP-2 necessitates supra-physiological doses of rhBMP-2 to achieve a robust osteogenic effect, which introduces risk of ectopic bone formation and severe inflammation and increases the cost. Although the concept that the ideal pharmacokinetics for rhBMP-2 includes both a burst and sustained release is generally accepted, investigations into the effects of the release kinetics on new bone formation are limited. In the present study, biodegradable polyurethane (PUR) and PUR/microsphere [PUR/poly(lactic-co-glycolic acid)] composite scaffolds with varying rhBMP-2 release kinetics were compared to the collagen sponge delivery system in a critical-sized rat segmental defect model. Microcomputed tomography analysis indicated that a burst followed by a sustained release of rhBMP-2 f...

Phase Stability of t′-Zirconia-Based Thermal Barrier Coatings: Mechanistic Insights

Abstract: The temperature capability of yttria-stabilized zirconia thermal barrier coatings (TBCs) is ultimately tied to the rate of evolution of the “nontransformable” t′ phase into a depleted tetragonal form predisposed to the monoclinic transformation on cooling. The t′ phase, however, has been shown to decompose in a small fraction of the time necessary to form the monoclinic phase. Instead, a modulated microstructure consisting of a coherent array of Y-rich and Y-lean lamellar phases develops early in the process, with mechanistic features suggestive of spinodal decomposition. Coarsening of this microstructure leads to loss of coherency and ultimately transformation into the monoclinic form, making the kinetics of this process, and not the initial decomposition, the critical factor in determining the phase stability of TBCs. Transmission electron microscopy is shown to be essential not only for characterizing the microstructure but also for proper interpretation of X-ray diffraction analysis.

Added features of hem/heg using gps technology

Abstract: A GPS-based energy management system for a home network is provided that includes a plurality of energy consuming devices The system comprises a central controller operatively connected to each energy consuming device, and one or more GPS-enabled devices configured to communicate with the central controller The central controller is programmed to modify the behavior of the energy consuming devices based on the location of at least one member of a home network

Motors/generators for traction /propulsion applications: A review

Abstract: There has been growing interest in electrification. This led to growing interest in hybrid/electrical traction applications. Many hybrid/electrical vehicles have been commercially introduced. Various technologies for the traction motors/generators have been developed. The requirements for motors/generators for hybrid/electrical traction applications are very demanding in terms of power density, efficiency, and cost. This paper will provide a comprehensive review of the state of the art highlighting the key global trends and tradeoff of various technologies. The paper will also discuss future trends and potential areas of research. The paper will cover light-duty vehicles (with more focus), medium- and heavy- duty vehicles, off highway vehicles, locomotives, and ship propulsion. The goal of the paper is to serve as a comprehensive reference for engineers working in the traction/propulsion area.

Accelerated diffusion spectrum imaging in the human brain using compressed sensing.

Abstract: We developed a novel method to accelerate diffusion spectrum imaging using compressed sensing. The method can be applied to either reduce acquisition time of diffusion spectrum imaging acquisition without losing critical information or to improve the resolution in diffusion space without increasing scan time. Unlike parallel imaging, compressed sensing can be applied to reconstruct a sub-Nyquist sampled dataset in domains other than the spatial one. Simulations of fiber crossings in 2D and 3D were performed to systematically evaluate the effect of compressed sensing reconstruction with different types of undersampling patterns (random, gaussian, Poisson disk) and different acceleration factors on radial and axial diffusion information. Experiments in brains of healthy volunteers were performed, where diffusion space was undersampled with different sampling patterns and reconstructed using compressed sensing. Essential information on diffusion properties, such as orientation distribution function, diffusion coefficient, and kurtosis is preserved up to an acceleration factor of R = 4. Magn Reson Med, 2011. © 2011 Wiley Periodicals, Inc.

Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data

Abstract: Given the pervasiveness of time series data in all human endeavors, and the ubiquity of clustering as a data mining application, it is somewhat surprising that the problem of time series clustering from a single stream remains largely unsolved. Most work on time series clustering considers the clustering of individual time series, e.g., gene expression profiles, individual heartbeats or individual gait cycles. The few attempts at clustering time series streams have been shown to be objectively incorrect in some cases, and in other cases shown to work only on the most contrived datasets by carefully adjusting a large set of parameters. In this work, we make two fundamental contributions. First, we show that the problem definition for time series clustering from streams currently used is inherently flawed, and a new definition is necessary. Second, we show that the Minimum Description Length (MDL) framework offers an efficient, effective and essentially parameter-free method for time series clustering. We show that our method produces objectively correct results on a wide variety of datasets from medicine, zoology and industrial process analyses.

Hadamard Matrix Analysis and Synthesis: With Applications to Communications and Signal/Image Processing

Abstract: Preface 1 Kronecker Matrix Algebra 2 A Hadamard Matrix 3 The Sylvester-Hadamard Matrix of Rank 2n 4 The Eigenvalues of Hn 5 The Eigenvectors of Hn 6 Other Constructions of Hn 7 The Hadamard Transform and its Fast Implementation 8 Use of the 1-D Hadamard Transform in the Computation of a 2-D Hadamard Transform 9 The Fast Fourier Transform and the Hadamard Transform 10 Computational Structures 11 Efficient Hadamard Transform Domain Computation 12 The Hadamard Transform in Statistics 13 The Hadamard Transform and Error-Correction Coding 14 Boolean Functions 15 Spectrally Preconditioned Threshold Logic 16 Synthesis of Bent Functions 17 The m-Sequence 18 Composite Sequences 19 The Thue-Morse Sequence 20 Signal Representation 21 A New Hadamard Basis and Its Implication for Signaling 22 A Stochastic Operator Field 23 A Naturalness Preserving Transform References Index

System and method for optimizing plant operations

Abstract: Embodiments of the present disclosure include systems and a method In one embodiment, a system is provided The system includes a risk calculation system configured to calculate a risk based on a static input and a dynamic input, and a decision support system configured to use the risk to derive a decision The system also includes a plant control system configured to update operations of a plant based on the decision, wherein the decision predicts future plant conditions

Pulse pileup statistics for energy discriminating photon counting x-ray detectors

Abstract: Purpose: Energy discriminating photon countingx-ray detectors can be subject to a wide range of flux rates if applied in clinical settings. Even when the incident rate is a small fraction of the detector’s maximum periodic rateN 0, pulse pileup leads to count rate losses and spectral distortion. Although the deterministic effects can be corrected, the detrimental effect of pileup on imagenoise is not well understood and may limit the performance of photon counting systems. Therefore, the authors devise a method to determine the detector count statistics and imaging performance. Methods: The detector count statistics are derived analytically for an idealized pileup model with delta pulses of a nonparalyzable detector. These statistics are then used to compute the performance (e.g., contrast-to-noise ratio) for both single material and material decomposition contrastdetection tasks via the Cramer-Rao lower bound (CRLB) as a function of the detector input count rate. With more realistic unipolar and bipolar pulse pileup models of a nonparalyzable detector, the imaging task performance is determined by Monte Carlo simulations and also approximated by a multinomial method based solely on the mean detected output spectrum. Photon counting performance at different count rates is compared with ideal energy integration, which is unaffected by count rate. Results: The authors found that an ideal photon countingdetector with perfect energy resolution outperforms energy integration for our contrastdetection tasks, but when the input count rate exceeds 20%N 0, many of these benefits disappear. The benefit with iodine contrast falls rapidly with increased count rate while water contrast is not as sensitive to count rates. The performance with a delta pulse model is overoptimistic when compared to the more realistic bipolar pulse model. The multinomial approximation predicts imaging performance very close to the prediction from Monte Carlo simulations. The monoenergetic image with maximum contrast-to-noise ratio from dual energy imaging with ideal photon counting is only slightly better than with dual kVp energy integration, and with a bipolar pulse model, energy integration outperforms photon counting for this particular metric because of the count rate losses. However, the material resolving capability of photon counting can be superior to energy integration with dual kVp even in the presence of pileup because of the energy information available to photon counting. Conclusions: A computationally efficient multinomial approximation of the count statistics that is based on the mean output spectrum can accurately predict imaging performance. This enables photon counting system designers to directly relate the effect of pileup to its impact on imaging statistics and how to best take advantage of the benefits of energy discriminating photon countingdetectors, such as material separation with spectral imaging.

Nerve-highlighting fluorescent contrast agents for image-guided surgery.

Abstract: Nerve damage is the major morbidity of many surgeries, resulting in chronic pain, loss of function, or both. The sparing of nerves during surgical procedures is a vexing problem because surrounding tissue often obscures them. To date, systemically administered nerve-highlighting contrast agents that can be used for nerve-sparing image-guided surgery have not been reported. In the current study, physicochemical and optical properties of 4,4'-[(2-methoxy-1,4-phenylene)di-(1E)-2,1-ethenediyl]bis-benzenamine (BMB) and a newly synthesized, red-shifted derivative 4-[(1E)-2-[4-[(1E)-2-[4-aminophenyl]ethenyl]-3-methoxyphenyl]ethenyl]-benzonitrile (GE3082) were characterized in vitro and in vivo. Both agents crossed the blood-nerve barrier and blood-brain barrier and rendered myelinated nerves fluorescent after a single systemic injection. Although both BMB and GE3082 also exhibited significant uptake in white adipose tissue, GE3082 underwent a hypsochromic shift in adipose tissue that provided a means to eliminate the unwanted signal using hyperspectral deconvolution. Dose and kinetic studies were performed in mice to determine the optimal dose and drug-imaging interval. The results were confirmed in rat and pig, with the latter used to demonstrate, for the first time, simultaneous fluorescence imaging of blood vessels and nerves during surgery using the FLARE™ (Fluorescence-Assisted Resection and Exploration) imaging system. These results lay the foundation for the development of ideal nerve-highlighting fluorophores for image-guided surgery.