Deformable Meshes for Medical Image Segmentation Accurate Automatic
Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author’s core met
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Among future technologies with high innovation potential, medical engineering counts among those with above-average growth rates and is considered crisesproof. Computerization, miniaturization, and molecularization are essential trends in medical engineering. Computerization is the basis for medical imaging, image processing, and image-guided methods in surgery. Miniaturization plays an important role in the field of intelligent implants, minimally invasive surgery as well as in the development of new nanostructured materials in medicine. Molecularization is both a crucial element in the field of regenerative medicine and the so called molecular imaging. Cross-sectional technologies like nano- and microsystems technology as well as optical technologies and softwaresystems are, therefore, of high relevance. This series for outstanding dissertations and habilitation treatises in the field of medical engineering covers clinical engineering and medical computer science as well as medical physics, biomedical engineering and medical engineering science. Editor-in-Chief: Prof. Dr. Thorsten M. Buzug Institut für Medizintechnik, Universität zu Lübeck Editorial Board: Prof. Dr. Olaf Dössel Institut für Biomedizinische Technik, Karlsruhe Institute for Technology Prof. Dr. Heinz Handels Institut für Medizinische Informatik, Universität zu Lübeck Prof. Dr.-Ing. Joachim Hornegger Lehrstuhl für Mustererkennung, Universität Erlangen-Nürnberg Prof. Dr. Marc Kachelrieß German Cancer Research Center, Heidelberg Prof. Dr. Edmund Koch, Klinisches Sensoring und Monitoring, TU Dresden
Prof. Dr.-Ing. Tim C. Lüth Micro Technology and Medical Device Technology, TU München Prof. Dr. Dietrich Paulus Institut für Computervisualistik, Universität Koblenz-Landau Prof. Dr. Bernhard Preim Institut für Simulation und Graphik, Universität Magdeburg Prof. Dr.-Ing. Georg Schmitz Lehrstuhl für Medizintechnik, Universität Bochum
Dagmar Kainmueller
Deformable Meshes for Medical Image Segmentation Accurate Automatic Segmentation of Anatomical Structures
Dagmar Kainmueller Max Planck Institute of Molecular Cell Biology and Genetics Dresden, Germany
Dissertation University of Lübeck, 2013
ISBN 978-3-658-07014-4 DOI 10.1007/978-3-658-07015-1
ISBN 978-3-658-07015-1 (eBook)
The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available in the Internet at http://dnb.d-nb.de. Library of Congress Control Number: 2014947962 Springer Vieweg © Springer Fachmedien Wiesbaden 2015 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. Exempted from this legal reservation are brief excerpts
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