Brain Warping

Brain Warping

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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.
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Product details

  • Audio | 385 pages
  • 224 x 288 x 24.1mm | 1,351.72g
  • Academic Press Inc
  • San Diego, United States
  • English
  • b&w and colour illustrations
  • 0126925356
  • 9780126925357

About Arthur W. Toga

Dr. Toga is a Professor of Neurology at the UCLA School of Medicine. He is also Director of the Laboratory of Neuro Imaging, which he founded and developed into one of the largest research neuroimaging centers in the world, and Co-Director of the UCLA Brain Mapping Division. With his diverse team, Dr. Toga has been responsible for a number of breakthroughs in various areas of neuroscience. He has published more than 170 papers, including chapters, textbooks, and reviews, and has received numerous honors and awards in computer science, graphics, and neuroscience. Dr. Toga holds the chairmanship of numerous committees within UCLA, NIH, and a variety of international task forces and is the founder and Co-Editor-in-Chief of NeuroImage, also published by Academic Press.
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Table of contents

A.W. Toga, An Introduction to Brain Warping.
J. Ashburner and K. Friston, Spatial Normalization.
Intensity Based Approaches:
R. Bajcsy, Elastic Deformation Utilizing a Mechanical System.
S. Kovacic, Multi-Resolution; Multiscale Approaches.
S. Warfield, A. Robatino, J. Dengler, F. Jolesz, and R. Kikinis, Nonlinear Registration and Template Driven Segmentation.
G. Christensen, M.I. Miller, and S.C. Joshi, Bayesian Framework for Image Registration Using Eigenfunctions.
J. Gee, Finite Element Methods.
M. Miller, S.C. Joshi, and G.E. Christensen, Large Deformation Fluid Diffeomorphisms for Landmark and Image Matching.
D.L. Collins and A.C. Evans, ANIMAL: Automatic Nonlinear Image Matching and Anatomical Labeling.
J.-P. Thirion, Diffusing Models and Applications.
F.L. Bookstein, Linear Methods for Nonlinear Maps.
H. Mueller and D. Ruprecht, Spatial Interpolants for Warping.
M.W. Vannier, Global Pattern Matching.
G. Subsol, Crest-Lines for Curve Based Warping.
D. Terzopolous, Snakes in Warping and Matching.
J.H. Downs III, J.L. Lancaster, and P.T. Fox, Surface Based Spatial Normalization Using Convex Hulls.
S. Lavallee, E. Bittar, and R. Szeliski, Elastic Registration and Inference Using Octree-Splines.
J.W. Haller, Brain Templates.
P. Thompson and A.W. Toga, Anatomically-Driven Strategies for High-Dimensional Brain Image Warping and Pathology Detection.
H. Drury, D.C. Van Essen, M. Corbetta, and A. Z. Snyder, Surface-Based Analyses of the Human Cerebral Cortex.
R.P. Woods, Automated Global Polynomial Warping.
Subject Index.
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