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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 / edited by Carole H. Sudre, Christian F. Baumgartner, Adrian Dalca, Chen Qin, Ryutaro Tanno, Koen Van Leemput, William M. Wells III
(Lecture Notes in Computer Science. ISSN:16113349 ; 13563)

データ種別	電子ブック
版	1st ed. 2022.
出版者	(Cham : Springer Nature Switzerland : Imprint: Springer)
出版年	2022
大きさ	X, 147 p. 39 illus., 32 illus. in color : online resource
著者標目	Sudre, Carole H editor Baumgartner, Christian F editor Dalca, Adrian editor Qin, Chen editor Tanno, Ryutaro editor Van Leemput, Koen editor Wells III, William M editor SpringerLink (Online service)

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0001278	Computer Scinece R0 2005-6,2022-3				9783031167492

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一般注記	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 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 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 HTTP:URL=https://doi.org/10.1007/978-3-031-16749-2
件　名	LCSH:Artificial intelligence LCSH:Image processing -- Digital techniques 全ての件名で検索 LCSH:Computer vision LCSH:Computers LCSH:Application software FREE:Artificial Intelligence FREE:Computer Imaging, Vision, Pattern Recognition and Graphics FREE:Computing Milieux FREE:Computer and Information Systems Applications
分　類	LCC:Q334-342 LCC:TA347.A78 DC23:006.3
書誌ID	EB00000666
ISBN	9783031167492