東華大學圖書館 |

Uncertainty for safe utilization of machine learning in medical imaging = 6th International Workshop, UNSURE 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Uncertainty for safe utilization of machine learning in medical imaging/ edited by Carole H. Sudre ... [et al.].
其他題名:	6th International Workshop, UNSURE 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings /
其他題名:	UNSURE 2024
其他作者:	Sudre, Carole H.
團體作者:	UNSURE (Workshop)
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xi, 226 p. :ill. (chiefly color), digital ;24 cm.
內容註:	Annotation Uncertainty. -- Uncertainty-Aware Bayesian Deep Learning with Noisy Training Labels for Epileptic Seizure Detection. -- Active Learning for Scribble-based Diffusion MRI Segmentation. -- FISHing in Uncertainty: Synthetic Contrastive Learning for Genetic Aberration Detection. -- Diagnose with Uncertainty Awareness: Diagnostic Uncertainty Encoding Framework for Radiology Report Generation. -- Clinical implementation of uncertainty modelling and risk management in clinical pipelines. -- Making Deep Learning Models Clinically Useful - Improving Diagnostic Confidence in Inherited Retinal Disease with Conformal Prediction. -- GUARDIAN: Guarding Against Uncertainty and Adversarial Risks in Robot-Assisted Surgeries. -- Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components. -- Conformal Performance Range Prediction for Segmentation Output Quality Control. -- Holistic Consistency for Subject-level Segmentation Quality Assessment in Medical Image Segmentation. -- Out of distribution and domain shift identification and management. -- CROCODILE: Causality aids RObustness via COntrastive DIsentangled LEarning. -- Image-conditioned Diffusion Models for Medical Anomaly Detection. -- Information Bottleneck-based Feature Weighting for Enhanced Medical Image Out-of-Distribution Detection. -- Beyond Heatmaps: A Comparative Analysis of Metrics for Anomaly Localization in Medical Images. -- Typicality excels Likelihood for Unsupervised Out-of-Distribution Detection in Medical Imaging. -- Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection. -- Uncertainty-Aware Vision Transformers for Medical Image Analysis. -- Uncertainty modelling and estimation. -- Efficient Precision control in Object Detection Models for Enhanced and Reliable Ovarian Follicle Counting. -- GLANCE: Combating Label Noise using Global and Local Noise Correction for Multi-Label Chest X-ray Classification. -- Conformal Prediction and Monte Carlo Inference for Addressing Uncertainty in Cervical Cancer Screening. -- INFORMER- Interpretability Founded Monitoring of Medical Image Deep Learning.
Contained By:	Springer Nature eBook
標題:	Diagnostic imaging - Congresses. - Data processing -
電子資源:	https://doi.org/10.1007/978-3-031-73158-7
ISBN:	9783031731587

Uncertainty for safe utilization of machine learning in medical imaging = 6th International Workshop, UNSURE 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings /
Uncertainty for safe utilization of machine learning in medical imaging6th International Workshop, UNSURE 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings /[electronic resource] :UNSURE 2024edited by Carole H. Sudre ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xi, 226 p. :ill. (chiefly color), digital ;24 cm. - Lecture notes in computer science,151671611-3349 ;. - Lecture notes in computer science ;15167..

Annotation Uncertainty. -- Uncertainty-Aware Bayesian Deep Learning with Noisy Training Labels for Epileptic Seizure Detection. -- Active Learning for Scribble-based Diffusion MRI Segmentation. -- FISHing in Uncertainty: Synthetic Contrastive Learning for Genetic Aberration Detection. -- Diagnose with Uncertainty Awareness: Diagnostic Uncertainty Encoding Framework for Radiology Report Generation. -- Clinical implementation of uncertainty modelling and risk management in clinical pipelines. -- Making Deep Learning Models Clinically Useful - Improving Diagnostic Confidence in Inherited Retinal Disease with Conformal Prediction. -- GUARDIAN: Guarding Against Uncertainty and Adversarial Risks in Robot-Assisted Surgeries. -- Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components. -- Conformal Performance Range Prediction for Segmentation Output Quality Control. -- Holistic Consistency for Subject-level Segmentation Quality Assessment in Medical Image Segmentation. -- Out of distribution and domain shift identification and management. -- CROCODILE: Causality aids RObustness via COntrastive DIsentangled LEarning. -- Image-conditioned Diffusion Models for Medical Anomaly Detection. -- Information Bottleneck-based Feature Weighting for Enhanced Medical Image Out-of-Distribution Detection. -- Beyond Heatmaps: A Comparative Analysis of Metrics for Anomaly Localization in Medical Images. -- Typicality excels Likelihood for Unsupervised Out-of-Distribution Detection in Medical Imaging. -- Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection. -- Uncertainty-Aware Vision Transformers for Medical Image Analysis. -- Uncertainty modelling and estimation. -- Efficient Precision control in Object Detection Models for Enhanced and Reliable Ovarian Follicle Counting. -- GLANCE: Combating Label Noise using Global and Local Noise Correction for Multi-Label Chest X-ray Classification. -- Conformal Prediction and Monte Carlo Inference for Addressing Uncertainty in Cervical Cancer Screening. -- INFORMER- Interpretability Founded Monitoring of Medical Image Deep Learning.

This book constitutes the refereed proceedings of the 6th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, on October 10, 2024. The 20 full papers presented in this book were carefully reviewed and selected from 28 submissions. They are organized in the following topical sections: annotation uncertainty; clinical implementation of uncertainty modelling and risk management in clinical pipelines; out of distribution and domain shift identification and management; uncertainty modelling and estimation.

ISBN: 9783031731587

Standard No.: 10.1007/978-3-031-73158-7doiSubjects--Topical Terms:

893542
Diagnostic imaging
--Data processing--Congresses.

LC Class. No.: RC78.7.D53

Dewey Class. No.: 616.0754

Uncertainty for safe utilization of machine learning in medical imaging = 6th International Workshop, UNSURE 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings /
LDR:04059nmm a2200361 a 4500 001 2407828
003 DE-He213
005 20241003131218.0
006 m d
007 cr nn 008maaau
008 260204s2025 sz s 0 eng d
020 $a 9783031731587 $q (electronic bk.)
020 $a 9783031731570 $q (paper)
024 7 $a 10.1007/978-3-031-73158-7 $2 doi
035 $a 978-3-031-73158-7
040 $a GP $c GP
041 0 $a eng
050 4 $a RC78.7.D53
072 7 $a UYT $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYT $2 thema
082 0 4 $a 616.0754 $2 23
090 $a RC78.7.D53 $b U59 2024
111 2 $a UNSURE (Workshop) $n (6th : $d 2024 : $c Marrakech, Morocco) $3 3779909
245 1 0 $a Uncertainty for safe utilization of machine learning in medical imaging $h [electronic resource] : $b 6th International Workshop, UNSURE 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings / $c edited by Carole H. Sudre ... [et al.].
246 3 $a UNSURE 2024
246 3 $a MICCAI 2024
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a xi, 226 p. : $b ill. (chiefly color), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 1611-3349 ; $v 15167
505 0 $a Annotation Uncertainty. -- Uncertainty-Aware Bayesian Deep Learning with Noisy Training Labels for Epileptic Seizure Detection. -- Active Learning for Scribble-based Diffusion MRI Segmentation. -- FISHing in Uncertainty: Synthetic Contrastive Learning for Genetic Aberration Detection. -- Diagnose with Uncertainty Awareness: Diagnostic Uncertainty Encoding Framework for Radiology Report Generation. -- Clinical implementation of uncertainty modelling and risk management in clinical pipelines. -- Making Deep Learning Models Clinically Useful - Improving Diagnostic Confidence in Inherited Retinal Disease with Conformal Prediction. -- GUARDIAN: Guarding Against Uncertainty and Adversarial Risks in Robot-Assisted Surgeries. -- Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components. -- Conformal Performance Range Prediction for Segmentation Output Quality Control. -- Holistic Consistency for Subject-level Segmentation Quality Assessment in Medical Image Segmentation. -- Out of distribution and domain shift identification and management. -- CROCODILE: Causality aids RObustness via COntrastive DIsentangled LEarning. -- Image-conditioned Diffusion Models for Medical Anomaly Detection. -- Information Bottleneck-based Feature Weighting for Enhanced Medical Image Out-of-Distribution Detection. -- Beyond Heatmaps: A Comparative Analysis of Metrics for Anomaly Localization in Medical Images. -- Typicality excels Likelihood for Unsupervised Out-of-Distribution Detection in Medical Imaging. -- Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection. -- Uncertainty-Aware Vision Transformers for Medical Image Analysis. -- Uncertainty modelling and estimation. -- Efficient Precision control in Object Detection Models for Enhanced and Reliable Ovarian Follicle Counting. -- GLANCE: Combating Label Noise using Global and Local Noise Correction for Multi-Label Chest X-ray Classification. -- Conformal Prediction and Monte Carlo Inference for Addressing Uncertainty in Cervical Cancer Screening. -- INFORMER- Interpretability Founded Monitoring of Medical Image Deep Learning.
520 $a This book constitutes the refereed proceedings of the 6th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, on October 10, 2024. The 20 full papers presented in this book were carefully reviewed and selected from 28 submissions. They are organized in the following topical sections: annotation uncertainty; clinical implementation of uncertainty modelling and risk management in clinical pipelines; out of distribution and domain shift identification and management; uncertainty modelling and estimation.
650 0 $a Diagnostic imaging $x Data processing $v Congresses. $3 893542
650 0 $a Artificial intelligence $x Medical applications $x Congresses. $3 660945
650 0 $a Machine learning $x Congresses. $3 576368
650 1 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Computing Milieux. $3 893243
650 2 4 $a Computer and Information Systems Applications. $3 3538505
700 1 $a Sudre, Carole H. $3 3503896
710 2 $a SpringerLink (Online service) $3 836513
711 2 $a International Conference on Medical Image Computing and Computer-Assisted Intervention $n (27th : $d 2024 : $c Marrakech, Morocco) $3 3724079
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 15167. $3 3779910
856 4 0 $u https://doi.org/10.1007/978-3-031-73158-7
950 $a Computer Science (SpringerNature-11645)