Pattern Classification of Medical Images: Computer Aided Diagnosis
This book presents advances in biomedical imaging analysis and processing techniques using time dependent medical image datasets for computer aided diagnosis. The analysis of time-series images is one of the most widely appearing problems in science, engi
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Xiao-Xia Yin Sillas Hadjiloucas Yanchun Zhang
Pattern Classification of Medical Images: Computer Aided Diagnosis
Health Information Science Series editor Yanchun Zhang
More information about this series at http://www.springer.com/series/11944
Xiao-Xia Yin Sillas Hadjiloucas Yanchun Zhang •
Pattern Classification of Medical Images: Computer Aided Diagnosis
123
Yanchun Zhang Victoria University Melbourne, VIC Australia
Xiao-Xia Yin Victoria University Melbourne, VIC Australia Sillas Hadjiloucas Biomedical Engineering, School of Biological Sciences University of Reading Reading UK
ISSN 2366-0988 Health Information Science ISBN 978-3-319-57026-6 DOI 10.1007/978-3-319-57027-3
ISSN 2366-0996
(electronic)
ISBN 978-3-319-57027-3
(eBook)
Library of Congress Control Number: 2017938557 © Springer International Publishing AG 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
This book discusses recent advances in biomedical sensing as well as image analysis and processing techniques so as to develop a unified framework for computer-aided disease diagnosis. One of the aims is to discuss different approaches that will enable us to efficiently and reliably identify different features that are present in biomedical images. Another aim is to provide a generic framework for image classification. The following four biomedical imaging modalities are considered: terahertz (THz) imaging, dynamic contrast-enhanced MRIs (DCE-MRIs) including functional MRI (fMRI), retinal fundus imaging and optical coherence tomography (OCT). THz imaging is chosen as it is a very promising emergent diagnostic modality that complements MRI. Under certain circumst
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