Automatic Localisation of Vertebrae in DXA Images Using Random Forest Regression Voting
We describe a method for automatic detection and localisation of vertebrae in clinical images that was designed to avoid making a priori assumptions of how many vertebrae are visible. Multiple random forest regressors were trained to identify vertebral en
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Tomaž Vrtovec · Jianhua Yao Ben Glocker · Tobias Klinder Alejandro Frangi · Guoyan Zheng Shuo Li (Eds.)
Computational Methods and Clinical Applications for Spine Imaging Third International Workshop and Challenge, CSI 2015 Held in Conjunction with MICCAI 2015 Munich, Germany, October 5, 2015, Revised Selected Papers
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Lecture Notes in Computer Science Commenced Publication in 1973 Founding and Former Series Editors: Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen
Editorial Board David Hutchison Lancaster University, Lancaster, 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, Zürich, Switzerland John C. Mitchell Stanford University, Stanford, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen TU Dortmund University, Dortmund, Germany Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max Planck Institute for Informatics, Saarbrücken, Germany
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More information about this series at http://www.springer.com/series/7412
Tomaž Vrtovec Jianhua Yao Ben Glocker Tobias Klinder Alejandro Frangi Guoyan Zheng Shuo Li (Eds.) •
•
•
Computational Methods and Clinical Applications for Spine Imaging Third International Workshop and Challenge, CSI 2015 Held in Conjunction with MICCAI 2015 Munich, Germany, October 5, 2015 Revised Selected Papers
123
Editors Tomaž Vrtovec University of Ljubljana Ljubljana Slovenia
Alejandro Frangi University of Sheffield Sheffield UK
Jianhua Yao National Institutes of Health Bethesda, MD USA
Guoyan Zheng University of Bern Bern Switzerland
Ben Glocker Imperial College London London UK
Shuo Li University of Western Ontario London, ON Canada
Tobias Klinder Philips GmbH Innovative Technologies Hamburg Germany
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-319-41826-1 ISBN 978-3-319-41827-8 (eBook) DOI 10.1007/978-3-319-41827-8 Library of Congress Control Number: 2016943824 LNCS Sublibrary: SL6 – Image Processing, Computer Vision, Pattern Recognition, and Graphics © Springer International Publishing Switzerland 2016 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 the
