Elsevier S & T

Brain Warping

Toga, Arthur W.

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Table of contents
  • Cover
  • Contentsv
  • Contributorsix
  • Prefacexi
  • Acknowledgmentsxiii
  • SECTION 1: OVERVIEW1
  • Chapter 1. An Introduction to Brain Warping1
  • Overview and Preliminaries1
  • Origins: A Historical Perspective3
  • Warping Strategies4
  • Applications6
  • Visualization16
  • Multidimensional Warping17
  • Summary22
  • References22
  • Chapter 2. Spatial Normalization27
  • Background27
  • Theory29
  • Mathematics30
  • Implementation33
  • Evaluation and Limitations39
  • Future Directions43
  • Conclusions44
  • References44
  • SECTION II: INTENSITY BASED APPROACHES45
  • Chapter 3. Multiscale/Multiresolution Representations45
  • Introduction45
  • Multiscale Basics47
  • Registration in a Multiscale Framework56
  • Some Multiscale Registration Schemes57
  • Conclusions63
  • References63
  • Chapter 4. Nonlinear Registration and Template-Driven Segmentation67
  • Introduction67
  • Nonlinear Registration Techniques68
  • Template-Driven Segmentation75
  • Results78
  • Discussion83
  • References83
  • Chapter 5. Bayesian Framework for Image Registration Using Eigenfunctions85
  • Background85
  • Theory86
  • Mathematics87
  • Implementation89
  • Results91
  • Assumptions and Limitations95
  • References98
  • Chapter 6. Numerical Methods for High-Dimensional Warps101
  • Introduction101
  • Broit's Iterative Solution101
  • The Finite Element Method104
  • Experimental Comparison of Methods110
  • Summary112
  • References113
  • Chapter 7. Large Deformation Fluid Diffeomorphisms for Landmark and Image Matching115
  • Background and History115
  • Theory for Generating Large Deformation Diffeomorphisms117
  • Algorithms and Implementation for Large Deformation Diffeomorphisms118
  • Results and Validation122
  • References130
  • Chapter 8. ANIMAL: Automatic Nonlinear Image Matching and Anatomical Labeling133
  • Introduction133
  • Background134
  • Methods135
  • Conclusion141
  • References141
  • Chapter 9. Diffusing Models and Applications143
  • Introduction143
  • Nonrigid Matching Viewed as an Attraction Problem143
  • Diffusing Models144
  • Implementations Derived from the Concept of Diffusing Models146
  • Experiments147
  • Applications149
  • Morphoanalysis153
  • Conclusion153
  • References153
  • Chapter 10. Linear Methods for Nonlinear Maps: Procrustes Fits, Thin-Plate Splines, and the Biometri157
  • Overview157
  • Introduction158
  • Some Geometric-Statistical Theory159
  • Implementations and Additional Linearizations165
  • Implications for Other Methodologies176
  • Concluding Comment: The Centrality of Careful Linearizations for Medical Image Analysis178
  • References180
  • SECTION III :GEOMETRICALLY BASED APPROACHES183
  • Chapter 11. Elastic Matching: Continuum Mechanical and Probabilistic Analysis183
  • Introduction183
  • Anatomy Atlas184
  • Elastic Matching184
  • Bayesian Generalization186
  • Applications192
  • Summary196
  • References196
  • Chapter 12. Spatial Interpolants for Warping199
  • Warping with Scattered Data Interpolation Methods199
  • Distance-Weighted Methods200
  • Radial Basis Functions203
  • Simplex-Based Methods205
  • Natural Neighbor Interpolation206
  • Extended Data207
  • Comparison of the Methods212
  • Warping of Shapes Described by Formulas and Meshes213
  • Warping of Raster Data216
  • References219
  • Chapter 13. Global Pattern Matching221
  • Background/History221
  • Theory224
  • Mathematics227
  • Implementation230
  • Validation/Acceptance/Assumptions/Limitations235
  • Future Directions237
  • Conclusions238
  • References238
  • Chapter 14. Crest Lines for Curve-Based Warping241
  • Landmarks of the Cortical Surface241
  • Crest Lines as Landmarks to Modelize Cortical Surface244
  • Three-Dimensional Nonrigid Registration of Crest Lines248
  • Three-Dimensional Warping Based on Crest Lines253
  • Conclusion258
  • References259
  • Chapter 15. Surface-Based Spatial Normalization Using Convex Hulls263
  • Background263
  • Theory265
  • Implementation269
  • Validation and Comparisons271
  • Future Directions280
  • Conclusions281
  • References281
  • Chapter 16. Elastic Registration and Inference Using Oct-Tree Splines283
  • Introduction283
  • Previous Work284
  • Problem Formulation285
  • Least Squares Minimization287
  • Fast Distance Computation288
  • Hierarchical Oct-Tree Spline Deformations289
  • Experimental Results291
  • Discussion and Conclusions293
  • References294
  • Chapter 17. Brain Templates297
  • Brain Images and Atlases297
  • The Concept of Brain Templates301
  • Theory303
  • Applications308
  • Limitations308
  • References309
  • Chapter 18. Anatomically Driven Strategies for High-Dimensional Brain Image Warping and Pathology De311
  • Challenges in Three-Dimensional Human Brain Mapping311
  • Classification of Warping Algorithms313
  • Cortical Surface Matching322
  • Pathology Detection326
  • Applications330
  • Conclusions333
  • References333
  • Chapter 19. Surface-Based Analyses of the Human Cerebral Cortex337
  • Introduction337
  • Surface Reconstruction338
  • A Surface-Based Atlas of the Human Cortex347
  • Visualization and Analysis of Experimental Data351
  • Compensating for Individual Variability353
  • Discussion358
  • References360
  • Appendix: Available Software and Data362
  • Chapter 20. Automated Global Polynomial Warping365
  • Background365
  • Automated Polynomial Warping Theory366
  • Mathematics and Implementation368
  • Validation and Comparison of Spatial Transformation Models371
  • Future Directions374
  • Conclusions376
  • References376
  • Index377
Book details
  • Vendor Elsevier S & T
  • SKU 9780126925357
  • ISBN-13 9780080525549
  • Author Toga, Arthur W.
  • Category Medical
  • Subject Neuroscience

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Description eBook delivery & access Reviews
Brain Warping is the premier book in the field of brain mapping to cover the mathematics, physics, computer science, and neurobiological issues related to brain spatial transformation and deformation correction. All chapters are organized in a similar fashion, covering the history, theory, and implementation of the specific approach discussed for ease of reading. Each chapter also discusses the computer science implementations, including descriptions of the programs and computer codes used in its execution. Readers of Brain Warping will be able to understand all of the approaches currently used in brain mapping, incorporating multimodality, and multisubject comparisons.

Key Features
* The only book of its kind
* Subject matter is the fastest growing area in the field of brain mapping
* Presents geometrically-based approaches to the field of brain mapping
* Discusses intensity-based approaches to the field of brain mapping