Computer Vision Approaches to Medical Image Analysis Second Internat
Medical imaging and medical image analysis are developing rapidly. While m- ical imaging has already become a standard of modern medical care, medical image analysis is still mostly performed visually and qualitatively. The ev- increasing volume of acquir
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Editorial Board David Hutchison Lancaster University, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Friedemann Mattern ETH Zurich, Switzerland John C. Mitchell Stanford University, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel Oscar Nierstrasz University of Bern, Switzerland C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen University of Dortmund, Germany Madhu Sudan Massachusetts Institute of Technology, MA, USA Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Moshe Y. Vardi Rice University, Houston, TX, USA Gerhard Weikum Max-Planck Institute of Computer Science, Saarbruecken, Germany
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Reinhard R. Beichel Milan Sonka (Eds.)
ComputerVisionApproaches to Medical Image Analysis Second International ECCV Workshop, CVAMIA 2006 Graz, Austria, May 12, 2006 Revised Papers
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Volume Editors Reinhard R. Beichel Graz University of Technology Institute for Computer Graphics and Vision Inffeldgasse 16/2, 8010 Graz, Austria E-mail: [email protected] Milan Sonka University of Iowa Department of Electrical and Computer Engineering Iowa City, IA 52242, USA E-mail: [email protected]
Library of Congress Control Number: 2006933642 CR Subject Classification (1998): I.4, I.2.10, I.3.5, I.5, J.3 LNCS Sublibrary: SL 6 – Image Processing, Computer Vision, Pattern Recognition, and Graphics ISSN ISBN-10 ISBN-13
0302-9743 3-540-46257-0 Springer Berlin Heidelberg New York 978-3-540-46257-6 Springer Berlin Heidelberg New York
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Preface
Medical imaging and medical image analysis are developing rapidly. While medical imaging has already become a standard of modern medical care, medical image analysis is still mostly performed visually and qualitatively. The everincreasing volume of acquired data makes it impossible to utilize them in full. Equally important, the visual approaches to medical image analysis are known to suffer from a lack of reproducibility. A significant research effort is devoted to developing algorithms for proces
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