Insight into Images: Principles and Practice for Segmentation, Registration, and Image Analysis

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Overview

A companion to the Insight Toolkit An introduction to the theory of modern medical image processing, including the analysis of data from - X-ray computer tomography, - magnetic resonance imaging, - nuclear medicine, - and ultrasound. Using an algorithmic approach, and providing the mathematical, statistical, or signal processing as needed for background, the authors describe the principles of all methods implemented in the Insight Toolkit (ITK), a freely available, open- source, object-oriented library. The emphasis is on providing intuitive descriptions of the principles and illustrative examples of results from the leading filtering, segmentation, and registration methods. This book covers the mathematical foundations of important techniques such as: - Statistical pattern recognition, - PDE-based nonlinear image filtering, - Markov random fields, - Level set methods, - Deformable models, - Mutual information, image-based registration - Non-rigid image data fusion With contributions from: Elsa Angelini, Brian Avants, Stephen Aylward, Ting Chen, Jeffrey Duda, Jim Gee, Luis Ibanez, Celina Imielinska, Yinpeng Jin, Jisung Kim, Bill Lorensen, Dimitris Metaxas, Lydia Ng, Punam Saha, George Stetten, Tessa Sundaram, Jay Udupa, Ross Whitaker, Terry Yoo, and Ying Zhuge. The Insight Toolkit is part of the Visible Human Project from the National Library of Medicine, with support from NIDCR, NINDS, NIMH, NEI, NSF, TATRC, NCI, and NIDCD.

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Product Details

  • ISBN-13: 9781568812175
  • Publisher: Taylor & Francis
  • Publication date: 8/15/2004
  • Edition description: New Edition
  • Pages: 410
  • Product dimensions: 6.00 (w) x 8.90 (h) x 0.60 (d)

Table of Contents

I Introduction and basics 1
1 Introduction 3
2 Basic image processing and linear operators 19
3 Statistics of pattern recognition 47
4 Nonlinear image filtering with partial differential equations 103
II Segmentation 119
5 Segmentation basics 121
6 Fuzzy connectedness 131
7 Markov random field models 181
8 Isosurfaces and level sets 193
9 Deformable models 219
III Registration 237
10 Medical image registration : concepts and implementation 239
11 Non-rigid image registration 307
IV Hybrid methods - mixed approaches to segmentation 349
12 Hybrid segmentation methods 351
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