Blind MRI Brain Lesion Inpainting Using Deep Learning
In brain image analysis many of the current pipelines are not robust to the presence of lesions which degrades their accuracy and robustness. For example, performance of classic medical image processing operations such as non-linear registration or segmen
- PDF / 38,376,903 Bytes
- 206 Pages / 439.37 x 666.142 pts Page_size
- 38 Downloads / 252 Views
Ninon Burgos David Svoboda Jelmer M. Wolterink Can Zhao (Eds.)
Simulation and Synthesis in Medical Imaging 5th International Workshop, SASHIMI 2020 Held in Conjunction with MICCAI 2020 Lima, Peru, October 4, 2020 Proceedings
Lecture Notes in Computer Science Founding Editors Gerhard Goos Karlsruhe Institute of Technology, Karlsruhe, Germany Juris Hartmanis Cornell University, Ithaca, NY, USA
Editorial Board Members Elisa Bertino Purdue University, West Lafayette, IN, USA Wen Gao Peking University, Beijing, China Bernhard Steffen TU Dortmund University, Dortmund, Germany Gerhard Woeginger RWTH Aachen, Aachen, Germany Moti Yung Columbia University, New York, NY, USA
12417
More information about this series at http://www.springer.com/series/7412
Ninon Burgos David Svoboda Jelmer M. Wolterink Can Zhao (Eds.) •
•
•
Simulation and Synthesis in Medical Imaging 5th International Workshop, SASHIMI 2020 Held in Conjunction with MICCAI 2020 Lima, Peru, October 4, 2020 Proceedings
123
Editors Ninon Burgos CNRS – Paris Brain Institute Paris, France
David Svoboda Masaryk University Brno, Czech Republic
Jelmer M. Wolterink University of Twente Enschede, The Netherlands
Can Zhao Johns Hopkins University Bethesda, MD, USA
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-59519-7 ISBN 978-3-030-59520-3 (eBook) https://doi.org/10.1007/978-3-030-59520-3 LNCS Sublibrary: SL6 – Image Processing, Computer Vision, Pattern Recognition, and Graphics © Springer Nature Switzerland AG 2020 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, expressed 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. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
The Medical Image Computing and Computer Assisted Intervention (MICCAI) community needs data with known ground truth to
