Editors:
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11046)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Conference series link(s): MLMI: International Workshop on Machine Learning in Medical Imaging
Conference proceedings info: MLMI 2018.
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Table of contents (47 papers)
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Front Matter
About this book
The 45 papers presented in this volume were carefully reviewed and selected from 82 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.
Keywords
- artificial intelligence
- automatic segmentations
- classification and regression trees
- convolutional neural networks
- generative adversarial networks
- image processing
- image quality
- image reconstruction
- image segmentation
- imaging systems
- machine learning
- medical images
- network architecture
- neural networks
- segmentation methods
- supervised learning
Editors and Affiliations
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Nanjing University, Nanjing, China
Yinghuan Shi
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617A, Science Library, Korea University, Seoul, Korea (Republic of)
Heung-Il Suk
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University of North Carolina at Chapel H, Chapel Hill, USA
Mingxia Liu
Bibliographic Information
Book Title: Machine Learning in Medical Imaging
Book Subtitle: 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings
Editors: Yinghuan Shi, Heung-Il Suk, Mingxia Liu
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-00919-9
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2018
Softcover ISBN: 978-3-030-00918-2Published: 15 September 2018
eBook ISBN: 978-3-030-00919-9Published: 14 September 2018
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XII, 409
Number of Illustrations: 16 b/w illustrations, 138 illustrations in colour
Topics: Image Processing and Computer Vision, Artificial Intelligence, Health Informatics, Data Mining and Knowledge Discovery