Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis 6th Joint International Workshops, CVII-STENT 2017 and Second International Workshop, LABELS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10–14, 2017, Proceedings /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Cardoso, M. Jorge (Editor), Arbel, Tal (Editor), Lee, Su-Lin (Editor), Cheplygina, Veronika (Editor), Balocco, Simone (Editor), Mateus, Diana (Editor), Zahnd, Guillaume (Editor), Maier-Hein, Lena (Editor), Demirci, Stefanie (Editor), Granger, Eric (Editor), Duong, Luc (Editor), Carbonneau, Marc-André (Editor), Albarqouni, Shadi (Editor), Carneiro, Gustavo (Editor)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Series: Lecture Notes in Computer Science, 10552
• Subjects: Computer science.; Health informatics.; Computer organization.; Artificial intelligence.; Image processing.; Computer Science.; Image Processing and Computer Vision.; Health Informatics.; Artificial Intelligence (incl. Robotics).; Computer Systems Organization and Communication Networks.
• Physical Description: XVI, 166 p. 73 illus. online resource.
• ISBN: 9783319675343
• ISSN: 0302-9743 ;

This book constitutes the refereed joint proceedings of the 6th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2017, and the Second International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 6 full papers presented at CVII-STENT 2017 and the 11 full papers presented at LABELS 2017 were carefully reviewed and selected. The CVII-STENT papers feature the state of the art in imaging, treatment, and computer-assisted intervention in the field of endovascular interventions. The LABELS papers present a variety of approaches for dealing with few labels, from transfer learning to crowdsourcing.