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024 7 _a10.1007/978-3-031-16749-2
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072 7 _aCOM004000
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245 1 0 _aUncertainty for Safe Utilization of Machine Learning in Medical Imaging
_h[electronic resource] :
_b4th International Workshop, UNSURE 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings /
_cedited by Carole H. Sudre, Christian F. Baumgartner, Adrian Dalca, Chen Qin, Ryutaro Tanno, Koen Van Leemput, William M. Wells III.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2022.
300 _aX, 147 p. 39 illus., 32 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
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490 1 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v13563
505 0 _aUncertainty 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.
520 _aThis 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.
650 0 _aArtificial intelligence.
_93407
650 0 _aImage processing
_xDigital techniques.
_94145
650 0 _aComputer vision.
_990083
650 0 _aComputers.
_98172
650 0 _aApplication software.
_990084
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
650 2 4 _aComputing Milieux.
_955441
650 2 4 _aComputer and Information Systems Applications.
_990085
700 1 _aSudre, Carole H.
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700 1 _aBaumgartner, Christian F.
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700 1 _aDalca, Adrian.
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700 1 _aQin, Chen.
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700 1 _aTanno, Ryutaro.
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700 1 _aVan Leemput, Koen.
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700 1 _aWells III, William M.
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aLecture Notes in Computer Science,
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856 4 0 _uhttps://doi.org/10.1007/978-3-031-16749-2
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