Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10541)
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 2017.
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About this book
The 44 full papers presented in this volume were carefully reviewed and selected from 63 submissions. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging. The workshop focuses on major trends and challenges in this area, and presents works aimed to identify new cutting-edge techniques and their use in medical imaging.
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Keywords
- classification and regression trees
- convolutional neural networks
- deep learning
- factorization methods
- generative adversarial networks
- image analysis
- image processing
- image segmentation
- learning networks
- learning systems
- machine learning
- medical image analysis
- multi-task learning
- neural networks
- shape representation
- supervised learning
Table of contents (44 papers)
Other volumes
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Machine Learning in Medical Imaging
Editors and Affiliations
Bibliographic Information
Book Title: Machine Learning in Medical Imaging
Book Subtitle: 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Proceedings
Editors: Qian Wang, Yinghuan Shi, Heung-Il Suk, Kenji Suzuki
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-319-67389-9
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Softcover ISBN: 978-3-319-67388-2Published: 07 September 2017
eBook ISBN: 978-3-319-67389-9Published: 06 September 2017
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XV, 391
Number of Illustrations: 134 b/w illustrations
Topics: Image Processing and Computer Vision, Software Engineering/Programming and Operating Systems, Health Informatics, Data Mining and Knowledge Discovery, Artificial Intelligence
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