Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences
Cardiac motion estimation and segmentation play important roles in quantitatively assessing cardiac function and diagnosing cardiovascular diseases. In this paper, we propose a novel deep learning method for joint estimation of motion and segmentation fro
- PDF / 182,732,947 Bytes
- 982 Pages / 439.37 x 666.142 pts Page_size
- 34 Downloads / 246 Views
Alejandro F. Frangi · Julia A. Schnabel Christos Davatzikos · Carlos Alberola-López Gabor Fichtinger (Eds.)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 21st International Conference Granada, Spain, September 16–20, 2018 Proceedings, Part II
123
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, Zurich, 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, Chennai, 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
11071
More information about this series at http://www.springer.com/series/7412
Alejandro F. Frangi Julia A. Schnabel Christos Davatzikos Carlos Alberola-López Gabor Fichtinger (Eds.) •
•
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 21st International Conference Granada, Spain, September 16–20, 2018 Proceedings, Part II
123
Editors Alejandro F. Frangi University of Leeds Leeds UK
Carlos Alberola-López Universidad de Valladolid Valladolid Spain
Julia A. Schnabel King’s College London London UK
Gabor Fichtinger Queen’s University Kingston, ON Canada
Christos Davatzikos University of Pennsylvania Philadelphia, PA USA
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-00933-5 ISBN 978-3-030-00934-2 (eBook) https://doi.org/10.1007/978-3-030-00934-2 Library of Congress Control Number: 2018909526 LNCS Sublibrary: SL6 – Image Processing, Computer Vision, Pattern Recognition, and Graphics © Springer Nature Switzerland AG 2018, corrected publication 2018 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
