Cover of Danail Stoyanov (EDT), Zeike Taylor (EDT), Simone Balocco (EDT), Raphael Sznitman (EDT), Anne Martel (EDT), Lena Maier-Hein (EDT), Luc Duong (EDT), Guillaume Zahnd (EDT), Stefanie Demirci (EDT), Shadi Albarqouni (EDT), Su-Lin Lee (EDT), Stefano Moriconi (EDT), Veronika Cheplygina (EDT), Diana Mateus (EDT), Emanuele Trucco (EDT), Eric Granger (EDT), Pierre Jannin (EDT): Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis

Danail Stoyanov (EDT), Zeike Taylor (EDT), Simone Balocco (EDT), Raphael Sznitman (EDT), Anne Martel (EDT), Lena Maier-Hein (EDT), Luc Duong (EDT), Guillaume Zahnd (EDT), Stefanie Demirci (EDT), Shadi Albarqouni (EDT), Su-Lin Lee (EDT), Stefano Moriconi (EDT), Veronika Cheplygina (EDT), Diana Mateus (EDT), Emanuele Trucco (EDT), Eric Granger (EDT), Pierre Jannin (EDT) Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis

7th Joint International Workshop, CVII-STENT 2018 and Third International Workshop, LABELS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings

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Springer International Publishing

2018

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978-3-030-01364-6

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This book constitutes the refereed joint proceedings of the 7th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2018, and the Third International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2018, held in conjunction with the 21th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 9 full papers presented at CVII-STENT 2017 and the 12 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.

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