Medical Images Segmentation Using Learned Priors
Objects of specific shapes in an image are typically segmented with a deformable model being zero level of a geometric-level set function specifying sign-alternate shortest distances to the object boundary from each pixel. The goal shapes are approximated
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Ayman El-Baz Rajendra Acharya U Andrew F. Laine Jasjit S. Suri l
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Editors
Multi Modality State-ofthe-Art Medical Image Segmentation and Registration Methodologies Volume II
Editors Ayman El-Baz University of Louisville Department of Bioengineering Louisville USA [email protected]
Rajendra Acharya U Ngee Ann Polytechnic School of Engineering Clementi Road 535 599489 Singapore Blk 7 Level 2 Singapore [email protected]
Andrew F. Laine Columbia University Department of Biomedical Engineering New York USA
Jasjit S. Suri Biomedical Technologies, Inc. Denver, CO, USA Global Biomedical Technologies, Inc. California, USA (Aff.) Idaho State University Pocatello, ID, USA [email protected]
ISBN 978-1-4419-8203-2 e-ISBN 978-1-4419-8204-9 DOI 10.1007/ 978-1-4419-8204-9 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2011924210 # Springer ScienceþBusiness Media, LLC 2011 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Ayman El-Baz would like to dedicate this book to his wife, daughter, son, mother, and father. Rajendra Acharya U would like to dedicate this book to his students, collaborators, and colleagues. Andrew F. Laine would like to dedicate this book to his late beloved father Jason Laine. Jasjit S. Suri would like to dedicate this book to his students and collaborators all over the world.
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Preface
Segmentation of medical images in 2-D, 3-D, and 4-D has taken new dimension. This is mainly because for real-time image guidance in diagnosis and therapeutics. The application of image/volume registration is prominently seen in reconstruction, multimodality fusion, and now propagating in atlas-based analysis. The focus of this book is to share the application of combined segmentation and registration in medical imaging. Some of the cutting edge topics in segmentation covered in the book are graph cut, energy minimization methods, cine loop processing in cardiac applications, parametric and geometric deformable models in combination with principal component analysis, breast mass classification, classification of thyroid lesions into benign and malignant using vasculature properties, classification of autistic versus nonautistic brain data sets, and geometric modeling for prosthesis design. Some of the adva
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