Overview
- Editors:
- Carole H. Sudre ORCID:https://orcid.org/0000-0001-5753-428X0,
- Christian F. Baumgartner ORCID:https://orcid.org/0000-0002-3629-43841,
- Adrian Dalca ORCID:https://orcid.org/0000-0002-8422-01362,
- Chen Qin ORCID:https://orcid.org/0000-0003-3417-30923,
- Ryutaro Tanno ORCID:https://orcid.org/0000-0002-8107-67304,
- Koen Van Leemput ORCID:https://orcid.org/0000-0001-6466-53095,
- …
- William M. Wells III6
- Carole H. Sudre
University College London, London, UK
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- Christian F. Baumgartner
University of Tübingen, Tübingen, Germany
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- Adrian Dalca
Massachusetts General Hospital, Charlestown, USA
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- Chen Qin
Imperial College London, London, UK
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- Ryutaro Tanno
Google DeepMind, London, UK
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- Koen Van Leemput
Technical University of Denmark, Kongens Lyngby, Denmark
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- William M. Wells III
Harvard Medical School, Boston, USA
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Part of the book series:Lecture Notes in Computer Science (LNCS, volume 13563)
Included in the following conference series:
Conference proceedings info: UNSURE 2022.
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Keywords
Table of contents (13 papers)
Front Matter
Pages i-xUncertainty Modelling
Front Matter
Pages 1-1MOrphologically-Aware Jaccard-Based ITerative Optimization (MOJITO) for Consensus Segmentation
- Dimitri Hamzaoui, Sarah Montagne, Raphaële Renard-Penna, Nicholas Ayache, Hervé Delingette
Pages 3-13Quantification of Predictive Uncertainty via Inference-Time Sampling
- Katarína Tóthová, Ľubor Ladický, Daniel Thul, Marc Pollefeys, Ender Konukoglu
Pages 14-25Uncertainty Categories in Medical Image Segmentation: A Study of Source-Related Diversity
- Luke Whitbread, Mark Jenkinson
Pages 26-35On the Pitfalls of Entropy-Based Uncertainty for Multi-class Semi-supervised Segmentation
- Martin Van Waerebeke, Gregory Lodygensky, Jose Dolz
Pages 36-46What Do Untargeted Adversarial Examples Reveal in Medical Image Segmentation?
- Gangin Park, Chunsan Hong, Bohyung Kim, Won Hwa Kim
Pages 47-56
Uncertainty Calibration
Front Matter
Pages 57-57Improved Post-hoc Probability Calibration for Out-of-Domain MRI Segmentation
- Cheng Ouyang, Shuo Wang, Chen Chen, Zeju Li, Wenjia Bai, Bernhard Kainz et al.
Pages 59-69Improving Error Detection in Deep Learning Based Radiotherapy Autocontouring Using Bayesian Uncertainty
- Prerak Mody, Nicolas F. Chaves-de-Plaza, Klaus Hildebrandt, Marius Staring
Pages 70-79Stochastic Weight Perturbations Along the Hessian: A Plug-and-Play Method to Compute Uncertainty
- Hariharan Ravishankar, Rohan Patil, Deepa Anand, Vanika Singhal, Utkarsh Agrawal, Rahul Venkataramani et al.
Pages 80-88Calibration of Deep Medical Image Classifiers: An Empirical Comparison Using Dermatology and Histopathology Datasets
- Jacob Carse, Andres Alvarez Olmo, Stephen McKenna
Pages 89-99
Annotation Uncertainty and Out of Distribution Management
Front Matter
Pages 101-101nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods
- Matthew Baugh, Jeremy Tan, Athanasios Vlontzos, Johanna P. Müller, Bernhard Kainz
Pages 103-112Generalized Probabilistic U-Net for Medical Image Segementation
- Ishaan Bhat, Josien P. W. Pluim, Hugo J. Kuijf
Pages 113-124Joint Paraspinal Muscle Segmentation and Inter-rater Labeling Variability Prediction with Multi-task TransUNet
- Parinaz Roshanzamir, Hassan Rivaz, Joshua Ahn, Hamza Mirza, Neda Naghdi, Meagan Anstruther et al.
Pages 125-134Information Gain Sampling for Active Learning in Medical Image Classification
- Raghav Mehta, Changjian Shui, Brennan Nichyporuk, Tal Arbel
Pages 135-145
Back Matter
Pages 147-147
Other volumes
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging
Editors and Affiliations
University College London, London, UK
Carole H. Sudre
University of Tübingen, Tübingen, Germany
Christian F. Baumgartner
Massachusetts General Hospital, Charlestown, USA
Adrian Dalca
Imperial College London, London, UK
Chen Qin
Google DeepMind, London, UK
Ryutaro Tanno
Technical University of Denmark, Kongens Lyngby, Denmark
Koen Van Leemput
Harvard Medical School, Boston, USA
William M. Wells III
Bibliographic Information
Book Title:Uncertainty for Safe Utilization of Machine Learning in Medical Imaging
Book Subtitle:4th International Workshop, UNSURE 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings
Editors:Carole H. Sudre, Christian F. Baumgartner, Adrian Dalca, Chen Qin, Ryutaro Tanno, Koen Van Leemput, William M. Wells III
Series Title:Lecture Notes in Computer Science
DOI:https://doi.org/10.1007/978-3-031-16749-2
Publisher:Springer Cham
eBook Packages:Computer Science,Computer Science (R0)
Copyright Information:The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Softcover ISBN:978-3-031-16748-5Published: 18 September 2022
eBook ISBN:978-3-031-16749-2Published: 17 September 2022
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number:1
Number of Pages:X, 147
Number of Illustrations:7 b/w illustrations, 32 illustrations in colour
Topics:Artificial Intelligence,Computer Imaging, Vision, Pattern Recognition and Graphics,Computing Milieux,Computer Applications
