Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis - Second International Workshop, UNSURE 2020, and Third International Workshop, GRAIL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings (Paperback, 1st ed. 2020)

This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic.For UNSURE 2020, 10 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. GRAIL 2020 accepted 10 papers from the 12 submissions received. The workshop aims to bring together scientists that use and develop graph-based models for the analysis of biomedical images and to encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Lecture Notes in Computer Science, 12443
Release date:	October 2020
First published:	2020
Editors:	Carole H. Sudre • Hamid Fehri • Tal Arbel • Christian F. Baumgartner • Adrian Dalca • Ryutaro Tanno • Koen Van Leemput • William M Wells • Aristeidis Sotiras • Bartlomiej Papiez
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	222
Edition:	1st ed. 2020
ISBN-13:	978-3-03-060364-9
Categories:	Books > Social sciences > General Books > Computing & IT > Applications of computing > Pattern recognition Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Computing & IT > Applications of computing > Image processing > General
LSN:	3-03-060364-4
Barcode:	9783030603649

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