Description
| Summary: | 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.
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| Item Description: | "Organized as a satellite event of the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2020) in Lima, Peru, which was held completely virtually due to the COVID-19 pandemic."--Preface
International conference proceedings.
Includes author index.
3.2 Epistemic Uncertainty with Bayesian Deep Image Prior. |
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| Physical Description: | 1 online resource (232 pages) |
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| ISBN: | 9783030603656
3030603652 |
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| Source of Description, Etc. Note: | Online resource; title from PDF title page (SpringerLink, viewed December 14, 2020). |
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