Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12450)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Included in the following conference series:
Conference proceedings info: MLMIR 2020.
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Table of contents(15 papers)
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Deep Learning for Magnetic Resonance Imaging
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Deep Learning for General Image Reconstruction
Other volumes
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Machine Learning for Medical Image Reconstruction
About this book
This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshop was held virtually.
The 15 papers presented were carefully reviewed and selected from 18 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging and deep learning for general image reconstruction.
Editors and Affiliations
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University of British Columbia, Vancouver, Canada
Farah Deeba
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New York University, New York City, USA
Patricia Johnson
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Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
Tobias Würfl
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Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)
Jong Chul Ye
Bibliographic Information
Book Title: Machine Learning for Medical Image Reconstruction
Book Subtitle: Third International Workshop, MLMIR 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings
Editors: Farah Deeba, Patricia Johnson, Tobias Würfl, Jong Chul Ye
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-61598-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Softcover ISBN: 978-3-030-61597-0Published: 20 October 2020
eBook ISBN: 978-3-030-61598-7Published: 21 October 2020
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: VIII, 163
Number of Illustrations: 28 b/w illustrations, 48 illustrations in colour
Topics: Artificial Intelligence, Image Processing and Computer Vision, Computer Appl. in Social and Behavioral Sciences, Computers and Education, Computational Biology/Bioinformatics