A Curriculum Learning Based Approach to Captioning Ultrasound Images
We present a novel curriculum learning approach to train a natural language processing (NLP) based fetal ultrasound image captioning model. Datasets containing medical images and corresponding textual descriptions are relatively rare and hence, smaller-si
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Yipeng Hu · Roxane Licandro · J. Alison Noble et al. (Eds.)
Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis First International Workshop, ASMUS 2020 and 5th International Workshop, PIPPI 2020 Held in Conjunction with MICCAI 2020 Lima, Peru, October 4–8, 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
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More information about this series at http://www.springer.com/series/7412
Yipeng Hu Roxane Licandro J. Alison Noble Jana Hutter Stephen Aylward Andrew Melbourne Esra Abaci Turk Jordina Torrents Barrena (Eds.) •
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Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis First International Workshop, ASMUS 2020 and 5th International Workshop, PIPPI 2020 Held in Conjunction with MICCAI 2020 Lima, Peru, October 4–8, 2020 Proceedings
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Editors Yipeng Hu University College London London, UK
Roxane Licandro TU Wien and Medical University of Vienna Vienna, Austria
J. Alison Noble University of Oxford Oxford, UK
Jana Hutter King’s College London London, UK
Stephen Aylward Kitware Inc. New York, NY, USA
Andrew Melbourne King’s College London London, UK
Esra Abaci Turk Harvard Medical School and Children’s Hospital Boston, MA, USA
Jordina Torrents Barrena Hewlett Packard Barcelona, Spain Universitat Pompeu Fabra Barcelona, Spain
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-60333-5 ISBN 978-3-030-60334-2 (eBook) https://doi.org/10.1007/978-3-030-60334-2 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 mat