Uncertainty for safe utilization of machine learning in medical imaging : 4th International Workshop, UNSURE 2022, held in conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings / Carole H. Sudre, Christian F. Baumgartner, Adrian Dalca, Chen Qin, Ryutaro Tanno, Koen Van Leemput, William M. Wells III (eds.).

This book constitutes the refereed proceedings of the Fourth Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2022, held in conjunction with MICCAI 2022. The conference was hybrid event held from Singapore. For this workshop, 13 papers from 22 submissions w...

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Bibliographic Details
Corporate Authors:	UNSURE (Workshop) Singapore ; Online), International Conference on Medical Image Computing and Computer-Assisted Intervention
Other Authors:	Sudre, Carole H. (Editor), Baumgartner, Christian (Professor of health care engineering) (Editor), Dalca, Adrian V. (Adrian Vasile) (Editor), Qin, Chen (Editor), Tanno, Ryutaro (Editor), Leemput, Koen van (Editor), Wells, William M., III (Editor)
Format:	eBook
Language:	English
Published:	Cham, Switzerland : Springer, 2022.
Series:	Lecture notes in computer science ; 13563.
Subjects:	Diagnostic imaging > Data processing > Congresses. Artificial intelligence > Medical applications > Congresses. Machine learning > Congresses. Artificial intelligence > Medical applications Diagnostic imaging > Data processing Machine learning Electronic books. proceedings (reports) Conference papers and proceedings Conference papers and proceedings. Actes de congrès.
Online Access:	Click for online access

Table of Contents:

Uncertainty Modelling
MOrphologically-aware Jaccard-based ITerative Optimization (MOJITO) for Consensus Segmentation
Quantification of Predictive Uncertainty via Inference-Time Sampling
Uncertainty categories in medical image segmentation: a study of source-related diversity.
On the pitfalls of entropy-based uncertainty for multi-class semi-supervised segmentation
What Do Untargeted Adversarial Examples Reveal In Medical Image Segmentation?.
Uncertainty calibration
Improved post-hoc probability calibration for out-of-domain MRI segmentation.
Improving error detection in deep learning-based radiotherapy autocontouring using Bayesian uncertainty
A Plug-and-Play Method to Compute Uncertainty
Calibration of Deep Medical Image Classifiers: An Empirical Comparison using Dermatology and Histopathology Datasets
Annotation uncertainty and out of distribution management
nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods
Generalized Probabilistic U-Net for medical image segmentation
Joint paraspinal muscle segmentation and inter-rater labeling variability prediction with multi-task TransUNet
Information Gain Sampling for Active Learning in Medical Image Classification.

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