Handbook of Medical Imaging: Processing and Analysis Management pdf

HANDBOOK OF MEDICAL IMAGING Editorial Advisory Board Dr. William Brody Dr. Elias Zerhouni President Chairman, Department of Radiology Johns Hopkins University and Radiological Science Johns Hopkins Medical Institutions Section Editors Dr. Rangaraj M. Rangayyan Dr. Richard A. Robb Department of Electrical and Computer Engineering Director, Biomedical Imaging Resource University of Calgary Mayo Foundation Dr. Roger P. Woods Dr. H. K. Huang Division of Brain Mapping Department of Radiology UCLA School of Medicine Childrens Hospital of Los Angeles/ University of Southern California Academic Press Series in Biomedical Engineering Joseph Bronzino, Series Editor The focus of this series will be twofold. First, the series will produce a set of core text/ references for biomedical engineering undergraduate and graduate courses. With biomedical engineers coming from a variety of engineering and biomedical backgrounds, it will be necessary to create new cross-disciplinary teaching and self-study books. Secondly, the series will also develop handbooks for each of the major subject areas of biomedical engineering. Joseph Bronzino, the series editor, is one of the most renowned biomedical engineers in the world. He is the Vernon Roosa Professor of Applied Science at Trinity College in Hartford, Connecticut. HANDBOOK OF MEDICAL IMAGING PROCESSING AND ANALYSIS Editor-in-Chief Isaac N. Bankman, PhD Applied Physics Laboratory Johns Hopkins University Laurel, Maryland San Diego / San Francisco / New York / Boston / London / Sydney / Tokyo This book is printed on acid-free paper. ? s Copyright # 2000 by Academic Press All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Requests for permission to make copies of any part of the work should be mailed to: Permissions Department, Harcourt, Inc., 6277 Sea Harbor Drive, Orlando, Florida, 32887-6777. ACADEMIC PRESS A Harcourt Science and Technology Company 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA http://www.academicpress.com Academic Press Harcourt Place, 32 Jamestown Road, London NW1 7BY, UK Library of Congress Catalog Card Number: 00-101315 International Standard Book Number: 0-12-077790-8 Printed in the United States of America 00 01 02 03 04 COB 9 8 7 6 5 4 3 2 1 To Lisa, Judy, and Danny Contents Foreword ix Preface xi Contributors xiii I Enhancement 1 Fundamental Enhancement Techniques Raman B. Paranjape. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Adaptive Image Filtering Carl-Fredrik Westin, Hans Knutsson, and Ron Kikinis. . . . . . . . . . . . . . . . . . . . . . . 19 3 Enhancement by Multiscale Nonlinear Operators Andrew Laine and Walter Huda . . . . . . . . . . . . . . . . . . . . 33 4 Medical Image Enhancement with Hybrid Filters Wei Qian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 II Segmentation 5 Overview and Fundamentals of Medical Image Segmentation Jadwiga Rogowska . . . . . . . . . . . . . . . . . . . . . 69 6 Image Segmentation by Fuzzy Clustering: Methods and Issues Melanie A. Sutton, James C. Bezdek, Tobias C. Cahoon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 7 Segmentation with Neural Networks Axel Wismu È ller, Frank Vietze, and Dominik R. Dersch . . . . . . . . . . . . . . 107 8 Deformable Models Tim McInerney and Demetri Terzopoulos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 9 Shape Constraints in Deformable Models Lawrence H. Staib, Xiaolan Zeng, James S. Duncan, Robert T. Schultz, and Amit Chakraborty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 10 Gradient Vector Flow Deformable Models Chenyang Xu and Jerry L. Prince . . . . . . . . . . . . . . . . . . . . . . . . 159 11 Fully Automated Hybrid Segmentation of the Brain M. Stella Atkins and Blair T. Mackiewich. . . . . . . . . . . . . 171 12 Volumetric Segmentation Alberto F. Goldszal and Dzung L. Pham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 13 Partial Volume Segmentation with Voxel Histograms David H. Laidlaw, Kurt W. Fleischer, and Alan H. Barr . . 195 III Quanti®cation 14 Two-Dimensional Shape and Texture Quanti®cation Isaac N. Bankman, Thomas S. Spisz, and Sotiris Pavlopoulos 215 15 Texture Analysis in Three Dimensions as a Cue to Medical Diagnosis Vassili A. Kovalev and Maria Petrou . . . . 231 16 Computational Neuroanatomy Using Shape Transformations Christos Davatzikos . . . . . . . . . . . . . . . . . . . . 249 17 Arterial Tree Morphometry Roger Johnson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 18 Image-Based Computational Biomechanics of the Musculoskeletal System Edmund Y. Chao, N. Inoue, J.J. Elias, and F.J. Frassica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 19 Three-Dimensional Bone Angle Quanti®cation Jens A. Richolt, Nobuhiko Hata, Ron Kikinis, Jens Kordelle, and Michael B. Millis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 20 Database Selection and Feature Extraction for Neural Networks Bin Zheng . . . . . . . . . . . . . . . . . . . . . . . . . 311 21 Quantitative Image Analysis for Estimation of Breast Cancer Risk Martin J. Yaffe, Jeffrey W. Byng, and Norman F. Boyd. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323 22 Classi®cation of Breast Lesions in Mammograms Yulei Jiang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 23 Quantitative Analysis of Cardiac Function Osman Ratib. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359 24 Image Processing and Analysis in Tagged Cardiac MRI William S. Kerwin, Nael F. Osman, and Jerry L. Prince . 375 25 Image Interpolation and Resampling Philippe The  venaz, Thierry Blu, and Michael Unser . . . . . . . . . . . . . . . . 393 IV Registration 26 Physical Basis of Spatial Distortions in Magnetic Resonance Images Peter Jezzard . . . . . . . . . . . . . . . . . . . . . 425 27 Physical and Biological Bases of Spatial Distortions in Positron Emission Tomography Images Magnus Dahlbom and Sung-Cheng (Henry) Huang. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439 28 Biological Underpinnings of Anatomic Consistency and Variability in the Human Brain N. Tzourio-Mazoyer, F. Crivello, M. Joliot, and B. Mazoyer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449 29 Spatial Transformation Models Roger P. Woods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 465 vii 30 Validation of Registration Accuracy Roger P. Woods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 491 31 Landmark-Based Registration Using Features Identi®ed Through Differential Geometry Xavier Pennec, Nicholas Ayache, and Jean-Philippe Thirion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 32 Image Registration Using Chamfer Matching Marcel Van Herk. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515 33 Within-Modality Registration Using Intensity-Based Cost Functions Roger P. Woods. . . . . . . . . . . . . . . . . . . . 529 34 Across-Modality Registration Using Intensity-Based Cost Functions Derek L.G. Hill and David J. Hawkes . . . . . 537 35 Talairach Space as a Tool for Intersubject Standardization in the Brain Jack L. Lancaster and Peter T. Fox . . . . . 555 36 Warping Strategies for Intersubject Registration Paul M. Thompson and Arthur W. Toga . . . . . . . . . . . . . . . . . 569 37 Optimizing the Resampling of Registered Images William F. Eddy and Terence K. Young . . . . . . . . . . . . . . . . . 603 38 Clinical Applications of Image Registration Robert Knowlton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 613 39 Registration for Image-Guided Surgery Eric Grimson and Ron Kikinis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 623 40 Image Registration and the Construction of Multidimensional Brain Atlases Arthur W. Toga and Paul M. Thompson. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 635 V Visualization 41 Visualization Pathways in Biomedicine Meiyappan Solaiyappan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 659 42 Three-Dimensional Visualization in Medicine and Biology Richard A. Robb . . . . . . . . . . . . . . . . . . . . . . . . . 685 43 Volume Visualization in Medicine Arie E. Kaufman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 713 44 Fast Isosurface Extraction Methods for Large Image Data Sets Yarden Livnat, Steven G. Parker, and Christopher R. Johnson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 731 45 Morphometric Methods for Virtual Endoscopy Ronald M. Summers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 747 VI Compression Storage and Communication 46 Fundamentals and Standards of Compression and Communication Stephen P. Yanek, Quentin E. Dolecek, Robert L. Holland, and Joan E. Fetter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 759 47 Medical Image Archive and Retrieval Albert Wong and Shyh-Liang Lou . . . . . . . . . . . . . . . . . . . . . . . . . . . . 771 48 Image Standardization in PACS Ewa Pietka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 783 49 Quality Evaluation for Compressed Medical Images: Fundamentals Pamela Cosman, Robert Gray, and Richard Olshen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 803 50 Quality Evaluation for Compressed Medical Images: Diagnostic Accuracy Pamela Cosman, Robert Gray, and Richard Olshen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 821 51 Quality Evaluation for Compressed Medical Images: Statistical Issues Pamela Cosman, Robert Gray, and Richard Olshen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 841 52 Three-Dimensional Image Compression with Wavelet Transforms Jun Wang and H.K. Huang . . . . . . . . . . . . . 851 53 Medical Image Processing and Analysis Software Thomas S. Spisz and Isaac N. Bankman . . . . . . . . . . . . . . . . 863 Index 895 viii Foreword The development of medical imaging over the past three decades has been truly revolutionary. For example, in cardi- ology specialized three-dimensional motion estimation algorithms allow myocardial motion and strain measurements using tagged cardiac magnetic resonance imaging. In mam- mography, shape and texture analysis techniques are used to facilitate the diagnosis of breast cancer and assess its risk. Three-dimensional volumetric visualization of CT and MRI data of the spine, internal organs and the brain has become the standard for routine patient diagnostic care. What is perhaps most remarkable about these advances in medical imaging is the fact that the challenges have required signi®cant innovation in computational techniques for nearly all aspects of image processing in various ®elds. The use of multiple imaging modalities on a single patient, for example MRI and PET, requires sophisticated algorithms for image registration and pattern matching. Automated recognition and diagnosis require image segmentation, quanti®cation and enhancement tools. Algorithms for image segmentation and visualization are employed broadly through many applications using all of the digital imaging modalities. And ®nally, the widespread availability of medical images in digital format has spurred the search for ef®cient and effective image compres- sion and communication methods. Advancing the frontiers of medical imaging requires the knowledge and application of the latest image manipulation methods. In Handbook of Medical Imaging, Dr. Bankman has assembled a comprehensive summary of the state-of-the-art in image processing and analysis tools for diagnostic and therapeutic applications of medical imaging. Chapters cover a broad spectrum of topics presented by authors who are highly expert in their respective ®elds. For all those who are working in this exciting ®eld, the Handbook should become a standard reference text in medical imaging. William R. Brody President, John Hopkins University ix [...]... journey of the Handbook was set on its course with the guidance of two distinguished leaders who served on the advisory board of the Handbook: William Brody, president of Johns Hopkins University, and Elias Zerhouni, director of the Radiology and Radiological Science Department at Hopkins I appreciate the vision and encouragement of Joel Claypool who initiated this Handbook at Academic Press and allowed... contrast because of the nature and superimposition of the soft tissues of the breast, which is compressed during the imaging procedure The small differences that may exist between normal and abnormal tissues are confounded by noise and artifacts, often making direct analysis of the acquired images dif®cult In all of the cases just mentioned, some improvement in the appearance and visual quality of the images,... Chapter 12 Silesian University of Technology Division of Biomedical Electronics PL 44-101 Gliwice, Poland Chapter 48 Center for Imaging Science Department of Electrical and Computer Engineering Johns Hopkins University Baltimore, MD 21218 Chapters 10, 24 Wei Qian Department of Radiology College of Medicine and the H Lee Mof®tt Cancer and Research Institute University of South Florida Tampa, FL 33612... the fundamental classes of algorithms: enhancement, segmentation, quanti®cation, registration, visualization, and a section that covers compression, storage, and communication The last chapter describes some software packages for medical image processing and analysis I Enhancement Enhancement algorithms are used to reduce image noise and increase the contrast of structures of interest In images where... with each other or with templates, many must be compressed and archived To assist visual interpretation of medical images, the international imaging community has developed numerous automated techniques which have their merits, limitations, and realm of application This Handbook presents concepts and digital techniques for processing and analyzing medical images after they have been generated or digitized... its own realm of applications Given the diverse nature of medical images and their associated problems, it would be dif®cult to prescribe a single method that can serve a range of problems An investigator is well advised to study the images and their enhancement needs, and to explore a range of techniques, each of which may individually satisfy a subset of the requirements A collection of processed... hardware and software speci®cally designed to facilitate visual inspection of medical and biological data In some cases such as volumetric data, visualization techniques are essential to enable effective visual inspection This section starts with the evolution of visualization techniques and presents the fundamental concepts and algorithms used for rendering, display, manipulation, and modeling of multidimensional... techniques, volume visualization, and virtual endoscopy are discussed in detail, and applications are illustrated in two and three dimensions VI Compression, Storage, and Communication Compression, storage, and communication of medical images are related functions for which demand has recently increased signi®cantly Medical images need to be stored in an ef®cient and convenient manner for subsequent... blurring of lines and edges A computationally ef®cient way of implementing shift-variant anisotropic ®lters based on a non-linear combination of shift-invariant ®lter responses is described 2 Multidimensional Spatial Frequencies and Filtering At a conceptual level, there is a great deal of similarity between 1D signal processing and signal processing in higher dimensions For example, the intuition and knowledge... University of West Florida Pensacola, FL 32514 Chapter 6 Thierry Blu Department of Electrical and Computer Engineering University of California at San Diego La Jolla, CA 92093-0407 Chapters 49, 50, 51 Fabrice Crivello Groupe d'Imagerie Neurofonctionelle (GIN)  Universite de Caen GIP Cyceron 14074 Caen Cedex, France Chapter 28 Magnus Dahlbom Division of Nuclear Medicine Department of Molecular and Medical . the Vernon Roosa Professor of Applied Science at Trinity College in Hartford, Connecticut. HANDBOOK OF MEDICAL IMAGING PROCESSING AND ANALYSIS Editor-in-Chief Isaac. methods. Advancing the frontiers of medical imaging requires the knowledge and application of the latest image manipulation methods. In Handbook of Medical Imaging, Dr.