Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11849)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Included in the following conference series:
Conference proceedings info: GLMI 2019.
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About this book
This book constitutes the refereed proceedings of the First International Workshop on Graph Learning in Medical Imaging, GLMI 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019.
The 21 full papers presented were carefully reviewed and selected from 42 submissions. The papers focus on major trends and challenges of graph learning in medical imaging and present original work aimed to identify new cutting-edge techniques and their applications in medical imaging.Similar content being viewed by others
Keywords
- artificial intelligence
- computer aided diagnosis
- computer networks
- computer systems
- computer vision
- deep learning
- graph theory
- image processing
- image reconstruction
- image segmentation
- machine learning
- mathematics
- medical image analysis
- medical imaging data analytics
- molecular imaging
- network architecture
- network protocols
- neural networks
- pattern recognition
- signal processing
Table of contents (21 papers)
Other volumes
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Graph Learning in Medical Imaging
Editors and Affiliations
Bibliographic Information
Book Title: Graph Learning in Medical Imaging
Book Subtitle: First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings
Editors: Daoqiang Zhang, Luping Zhou, Biao Jie, Mingxia Liu
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-35817-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Softcover ISBN: 978-3-030-35816-7Published: 14 November 2019
eBook ISBN: 978-3-030-35817-4Published: 13 November 2019
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: IX, 182
Number of Illustrations: 19 b/w illustrations, 68 illustrations in colour
Topics: Artificial Intelligence, Image Processing and Computer Vision, Pattern Recognition, Computer Appl. in Social and Behavioral Sciences