Nonrigid registration using free-form deformations: application to breast MR images

doi:10.1109/42.796284

Home
/
Papers
/
Nonrigid registration using free-form deformations: application to breast MR images

Journal Article•DOI•

Nonrigid registration using free-form deformations: application to breast MR images

Daniel Rueckert¹, L.I. Sonoda, Carmel Hayes, Derek L. G. Hill, Martin O. Leach, David J. Hawkes - Show less +2 more•Institutions (1)

King's College London¹

30 Jul 1999-IEEE Transactions on Medical Imaging (IEEE Trans Med Imaging)-Vol. 18, Iss: 8, pp 712-721

TL;DR: The results clearly indicate that the proposed nonrigid registration algorithm is much better able to recover the motion and deformation of the breast than rigid or affine registration algorithms.

read less

Abstract: In this paper the authors present a new approach for the nonrigid registration of contrast-enhanced breast MRI. A hierarchical transformation model of the motion of the breast has been developed. The global motion of the breast is modeled by an affine transformation while the local breast motion is described by a free-form deformation (FFD) based on B-splines. Normalized mutual information is used as a voxel-based similarity measure which is insensitive to intensity changes as a result of the contrast enhancement. Registration is achieved by minimizing a cost function, which represents a combination of the cost associated with the smoothness of the transformation and the cost associated with the image similarity. The algorithm has been applied to the fully automated registration of three-dimensional (3-D) breast MRI in volunteers and patients. In particular, the authors have compared the results of the proposed nonrigid registration algorithm to those obtained using rigid and affine registration techniques. The results clearly indicate that the nonrigid registration algorithm is much better able to recover the motion and deformation of the breast than rigid or affine registration algorithms.

...read moreread less

Content maybe subject to copyright Report

Citations

PDF

Open Access

More filters

Journal Article•DOI•

Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data.

[...]

Stephen M. Smith¹, Mark Jenkinson¹, Heidi Johansen-Berg¹, Daniel Rueckert², Thomas E. Nichols³, Clare E. Mackay¹, Kate E. Watkins¹, Olga Ciccarelli⁴, M Z Cader¹, Paul M. Matthews¹, Timothy E.J. Behrens¹ - Show less +7 more•Institutions (4)

University of Oxford¹, Imperial College London², University of Michigan³, University College London⁴

15 Jul 2006-NeuroImage

TL;DR: TBSS aims to improve the sensitivity, objectivity and interpretability of analysis of multi-subject diffusion imaging studies by solving the question of how to align FA images from multiple subjects in a way that allows for valid conclusions to be drawn from the subsequent voxelwise analysis.

...read moreread less

5,959 citations

Journal Article•DOI•

New advances in the Clinica software platform for clinical neuroimaging studies

[...]

Alexandre Routier, Arnaud Marcoux, Mauricio Diaz Melo, Jérémy Guillon, Jorge Samper-González, Junhao Wen, Simona Bottani, Alexis Guyot, Elina Thibeau-Sutre, Marc Teichmann, Marie-Odile Habert, Stanley Durrleman, Ninon Burgos, Olivier Colliot - Show less +10 more

09 Jun 2019-NeuroImage

5,150 citations

Journal Article•DOI•

Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain.

[...]

Brian B. Avants¹, Charles L. Epstein¹, Murray Grossman¹, James C. Gee¹•Institutions (1)

University of Pennsylvania¹

01 Feb 2008-Medical Image Analysis

TL;DR: This study indicates that SyN, with cross-correlation, is a reliable method for normalizing and making anatomical measurements in volumetric MRI of patients and at-risk elderly individuals.

...read moreread less

4,233 citations

Cites background from "Nonrigid registration using free-fo..."

...The mutual information (MI) similarity metric garnered significant interest in recent years (Maes et al., 1997; Wells et al., 1997; Rueckert et al., 1999; Studholme et al., 2006)....
[...]
...Diffeomorphic image registration algorithms hold the promise of being able to deal successfully with both small (Bajcsy et al., 1983; Gee et al., 1993; Gee and Bajcsy, 1999; Peckar et al., 1998; Rueckert et al., 1999; Rogelj and Kovacic, 2006; Ashburner et al., 2000) and large deformation problems (Trouv’e, 1998; Christensen et al....
[...]
...…the promise of being able to deal successfully with both small (Bajcsy et al., 1983; Gee et al., 1993; Gee and Bajcsy, 1999; Peckar et al., 1998; Rueckert et al., 1999; Rogelj and Kovacic, 2006; Ashburner et al., 2000) and large deformation problems (Trouv’e, 1998; Christensen et al., 1997;…...
[...]

Journal Article•DOI•

A reproducible evaluation of ANTs similarity metric performance in brain image registration.

[...]

Brian B. Avants¹, Nicholas J. Tustison¹, Gang Song¹, Philip A. Cook¹, Arno Klein², James C. Gee¹ - Show less +2 more•Institutions (2)

University of Pennsylvania¹, Columbia University²

01 Feb 2011-NeuroImage

TL;DR: This is the first study to use a consistent transformation framework to provide a reproducible evaluation of the isolated effect of the similarity metric on optimal template construction and brain labeling, and to quantify the similarity of templates derived from different subgroups.

...read moreread less

3,491 citations

Cites background from "Nonrigid registration using free-fo..."

...Elastic-typemodels such asHAMMER (Shen andDavatzikos, 2002), statistical parametricmapping (SPM) (Ashburner and Friston, 2000), free-form deformations (FFD) (Rueckert et al., 1999), and Thirion's Demons (Thirion, 1998) operate in the space of vector fields, which does not preserve topology....
[...]
...…Ashburner, 2007; Vercauteren et al., 2009), cross-correlation (Gee, 1999; Ardekani et al., 2005; Avants et al., 2008), and mutual information (Viola and Wells, 1997; Rueckert et al., 1999; D'Agostino et al., 2003; Crum et al., 2003; Rogelj and Kovacic, 2006; Tao et al., 2009; Loeckx et al., 2010)....
[...]
...ANTs users may set parameters such that discretized FFD strategies and diffeomorphisms are combined....
[...]
...The same regularization scheme is available for both diffeomorphic and the recent directly manipulated free-form deformation (DMFFD) (Tustison et al., 2009a) registration....
[...]

Journal Article•DOI•

elastix : A Toolbox for Intensity-Based Medical Image Registration

[...]

Stefan Klein¹, Marius Staring¹, Keelin Murphy¹, Max A. Viergever¹, Josien P. W. Pluim¹ - Show less +1 more•Institutions (1)

Utrecht University¹

01 Jan 2010-IEEE Transactions on Medical Imaging

TL;DR: The software consists of a collection of algorithms that are commonly used to solve medical image registration problems, and allows the user to quickly configure, test, and compare different registration methods for a specific application.

...read moreread less

Abstract: Medical image registration is an important task in medical image processing. It refers to the process of aligning data sets, possibly from different modalities (e.g., magnetic resonance and computed tomography), different time points (e.g., follow-up scans), and/or different subjects (in case of population studies). A large number of methods for image registration are described in the literature. Unfortunately, there is not one method that works for all applications. We have therefore developed elastix, a publicly available computer program for intensity-based medical image registration. The software consists of a collection of algorithms that are commonly used to solve medical image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. The command-line interface enables automated processing of large numbers of data sets, by means of scripting. The usage of elastix for comparing different registration methods is illustrated with three example experiments, in which individual components of the registration method are varied.

...read moreread less

3,444 citations

Cites background or methods from "Nonrigid registration using free-fo..."

...several parametric nonrigid transformation models have been proposed [3], [28], [30], [32], [36], [37], each having its own advantages and disadvantages....
[...]
...Other examples of regularization terms are the bending energy of a thin plate [3] and the rigidity penalty term [2]....
[...]
...In elastix a B-spline representation [3] has been implemented and several physics-based spline models [30], [52], such as the thin-plate spline and the elastic body spline....
[...]

1
2
3
4
…
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
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
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200

Collapse

References

PDF

Open Access

More filters

Book•

Spline models for observational data

[...]

Grace Wahba

01 Mar 1990

TL;DR: In this paper, a theory and practice for the estimation of functions from noisy data on functionals is developed, where convergence properties, data based smoothing parameter selection, confidence intervals, and numerical methods are established which are appropriate to a number of problems within this framework.

...read moreread less

Abstract: This book serves well as an introduction into the more theoretical aspects of the use of spline models. It develops a theory and practice for the estimation of functions from noisy data on functionals. The simplest example is the estimation of a smooth curve, given noisy observations on a finite number of its values. Convergence properties, data based smoothing parameter selection, confidence intervals, and numerical methods are established which are appropriate to a number of problems within this framework. Methods for including side conditions and other prior information in solving ill posed inverse problems are provided. Data which involves samples of random variables with Gaussian, Poisson, binomial, and other distributions are treated in a unified optimization context. Experimental design questions, i.e., which functionals should be observed, are studied in a general context. Extensions to distributed parameter system identification problems are made by considering implicitly defined functionals.

...read moreread less

6,120 citations

"Nonrigid registration using free-fo..." refers background in this paper

...The general form of such a penalty term has been described by Wahba [28]....
[...]
...[28] G. Wahba, “Spline models for observational data,”Soc....
[...]
...Note that the regularization term is zero for any affine transformations and, therefore, penalizes only nonaffine transformations [28]....
[...]

Journal Article•DOI•

Principal warps: thin-plate splines and the decomposition of deformations

[...]

Fred L. Bookstein¹•Institutions (1)

University of Michigan¹

01 Jun 1989-IEEE Transactions on Pattern Analysis and Machine Intelligence

TL;DR: The decomposition of deformations by principal warps is demonstrated and the method is extended to deal with curving edges between landmarks to aid the extraction of features for analysis, comparison, and diagnosis of biological and medical images.

...read moreread less

Abstract: The decomposition of deformations by principal warps is demonstrated. The method is extended to deal with curving edges between landmarks. This formulation is related to other applications of splines current in computer vision. How they might aid in the extraction of features for analysis, comparison, and diagnosis of biological and medical images in indicated. >

...read moreread less

5,065 citations

"Nonrigid registration using free-fo..." refers background in this paper

...In contrast to thin-plate splines [25] or elastic-body splines [26], B-splines are locally controlled, which makes them computationally efficient even for a large number of control points....
[...]

Journal Article•DOI•

Multimodality image registration by maximization of mutual information

[...]

Frederik Maes¹, A Collignon¹, Dirk Vandermeulen¹, Guy Marchal¹, Paul Suetens¹ - Show less +1 more•Institutions (1)

Katholieke Universiteit Leuven¹

01 Apr 1997-IEEE Transactions on Medical Imaging

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.

...read moreread less

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.

...read moreread less

4,773 citations

"Nonrigid registration using free-fo..." refers background in this paper

...In particular, voxel-based similarity measures based on joint entropy [9], mutual information [10]–[13], and normalized mutual information [14], [15] have been shown to align images acquired with different imaging modalities, robustly....
[...]

Journal Article•DOI•

A survey of medical image registration.

[...]

J. B. Antoine Maintz¹, Max A. Viergever¹•Institutions (1)

Utrecht University¹

01 Mar 1998-Medical Image Analysis

TL;DR: A survey of recent publications concerning medical image registration techniques is presented, according to a model based on nine salient criteria, the main dichotomy of which is extrinsic versus intrinsic methods.

...read moreread less

3,426 citations

Journal Article•DOI•

An overlap invariant entropy measure of 3D medical image alignment

[...]