Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11861)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Included in the following conference series:
Conference proceedings info: MLMI 2019.
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About this book
The 78 papers presented in this volume were carefully reviewed and selected from 158 submissions.
They focus on major trends and challenges in the area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.
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Table of contents (78 papers)
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Machine Learning in Medical Imaging
Editors and Affiliations
Bibliographic Information
Book Title: Machine Learning in Medical Imaging
Book Subtitle: 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings
Editors: Heung-Il Suk, Mingxia Liu, Pingkun Yan, Chunfeng Lian
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-32692-0
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Softcover ISBN: 978-3-030-32691-3Published: 10 October 2019
eBook ISBN: 978-3-030-32692-0Published: 09 October 2019
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XVIII, 695
Number of Illustrations: 65 b/w illustrations, 245 illustrations in colour
Topics: Image Processing and Computer Vision, Artificial Intelligence