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Book Categories |
Contributors | ||
Preface | ||
Acknowledgments | ||
Sect. I | Overview | |
1 | An Introduction to Brain Warping | |
2 | Spatial Normalization | |
Sect. II | Intensity Based Approaches | |
3 | Multiscale/Multiresolution Representations | |
4 | Nonlinear Registration and Template-Driven Segmentation | |
5 | Bayesian Framework for Image Registration Using Eigenfunctions | |
6 | Numerical Methods for High-Dimensional Warps | |
7 | Large Deformation Fluid Diffeomorphisms for Landmark and Image Matching | |
8 | ANIMAL: Automatic Nonlinear Image Matching and Anatomical Labeling | |
9 | Diffusing Models and Applications | |
10 | Linear Methods for Nonlinear Maps: Procrustes Fits, Thin-Plate Splines, and the Biometric Analysis of Shape Variability | |
Sect. III | Geometrically Based Approaches | |
11 | Elastic Matching: Continuum Mechanical and Probabilistic Analysis | |
12 | Spatial Interpolants for Warping | |
13 | Global Pattern Matching | |
14 | Crest Lines for Curve-Based Warping | |
15 | Surface-Based Spatial Normalization Using Convex Hulls | |
16 | Elastic Registration and Inference Using Oct-Tree Splines | |
17 | Brain Templates | |
18 | Anatomically Driven Strategies for High-Dimensional Brain Image Warping and Pathology Detection | |
19 | Surface-Based Analyses of the Human Cerebral Cortex | |
20 | Automated Global Polynomial Warping | |
Index |
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