TY  - GEN
N2  - 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.
AB  - 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.
T1  - 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 /
AU  - Sudre, Carole H.,
AU  - Fehri, Hamid.,
AU  - Arbel, Tal,
AU  - Baumgartner, Christian F.,
AU  - Dalca, Adrian.,
AU  - Tanno, Ryutaro.,
AU  - Van Leemput, Koen.,
AU  - Wells, William M.,
AU  - Sotiras, Aristeidis.,
AU  - Papiez, Bartlomiej.,
AU  - Ferrante, Enzo.,
AU  - Parisot, Sarah.,
VL  - 12443
CN  - RC78.7.D53
N1  - "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
N1  - International conference proceedings.
N1  - Includes author index.
ID  - 945196
KW  - Diagnostic imaging
KW  - Artificial intelligence
KW  - Machine learning
SN  - 9783030603656
SN  - 3030603652
TI  - 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 /
LK  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-60365-6
UR  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-60365-6
ER  -