Graph Learning in Medical Imaging First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Zhang, Daoqiang (Editor, http://id.loc.gov/vocabulary/relators/edt), Zhou, Luping (Editor, http://id.loc.gov/vocabulary/relators/edt), Jie, Biao (Editor, http://id.loc.gov/vocabulary/relators/edt), Liu, Mingxia (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11849
• Subjects: Artificial intelligence.; Optical data processing.; Pattern recognition.; Application software.; Artificial Intelligence.; Image Processing and Computer Vision.; Pattern Recognition.; Computer Appl. in Social and Behavioral Sciences.
• Physical Description: IX, 182 p. 87 illus., 68 illus. in color. online resource.
• ISBN: 9783030358174
• DOI: 10.1007/978-3-030-35817-4

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.