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ORCIDUNSURE@MICCAI 2024: Marrakesh, Morocco
- Carole H. Sudre
, Raghav Mehta, Cheng Ouyang, Chen Qin, Marianne Rakic, William M. Wells III:
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. Lecture Notes in Computer Science 15167, Springer 2025, ISBN 978-3-031-73157-0
Annotation Uncertainty
- Deeksha M. Shama, Archana Venkataraman:
Uncertainty-Aware Bayesian Deep Learning with Noisy Training Labels for Epileptic Seizure Detection. 3-13 - Jonathan Lennartz, Golo Pohl, Thomas Schultz:
Active Learning for Scribble-Based Diffusion MRI Segmentation. 14-22 - Simon Gutwein, Martin Kampel, Sabine Taschner-Mandl, Roxane Licandro:
FISHing in Uncertainty: Synthetic Contrastive Learning for Genetic Aberration Detection. 23-33 - Sixing Yan, Haiyan Yin, Ivor W. Tsang, William K. Cheung:
Diagnose with Uncertainty Awareness: Diagnostic Uncertainty Encoding Framework for Radiology Report Generation. 34-44
Clinical Implementation of Uncertainty Modelling and Risk Management in Clinical Pipelines
- Biraja Ghoshal, William Woof, Bernardo Mendes, Saoud Al-Khuzaei, Thales Antonio Cabral De Guimaraes, Malena Daich Varela, Yichen Liu, Sagnik Sen, Siying Lin, Mital Shah, Yu Fujinami-Yokokawa, Andrew R. Webster, Omar A. Mahroo, Kaoru Fujinami, Frank G. Holz, Philipp Herrmann, Juliana Sallum, Konstantinos Balaskas, Savita Madhusudhan, Susan M. Downes, Michel Michaelides, Nikolas Pontikos:
Making Deep Learning Models Clinically Useful - Improving Diagnostic Confidence in Inherited Retinal Disease with Conformal Prediction. 47-58 - Ufaq Khan, Umair Nawaz, Tooba T. Sheikh, Asif Hanif, Mohammad Yaqub:
GUARDIAN: Guarding Against Uncertainty and Adversarial Risks in Robot-Assisted Surgeries. 59-69 - Hermione Warr, Yasin Ibrahim, Daniel R. McGowan, Konstantinos Kamnitsas:
Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components. 70-80 - Anna M. Wundram, Paul Fischer, Michael Mühlebach, Lisa M. Koch, Christian F. Baumgartner:
Conformal Performance Range Prediction for Segmentation Output Quality Control. 81-91 - Yizhe Zhang, Tao Zhou, Qiang Chen, Qi Dou, Shuo Wang:
Holistic Consistency for Subject-Level Segmentation Quality Assessment in Medical Image Segmentation. 92-102
Out of Distribution and Domain Shift Identification and Management
- Gianluca Carloni, Sotirios A. Tsaftaris, Sara Colantonio:
CROCODILE: Causality Aids RObustness via COntrastive DIsentangled LEarning. 105-116 - Matthew Baugh, Hadrien Reynaud, Sergio Naval Marimont, Sarah Cechnicka, Johanna P. Müller, Giacomo Tarroni, Bernhard Kainz:
Image-Conditioned Diffusion Models for Medical Anomaly Detection. 117-127 - Brayden Schott, Zan Klanecek, Alison Deatsch, Victor Santoro-Fernandes, Thomas Francken, Scott Perlman, Robert Jeraj:
Information Bottleneck-Based Feature Weighting for Enhanced Medical Image Out-of-Distribution Detection. 128-137 - David Zimmerer, Klaus H. Maier-Hein:
Beyond Heatmaps: A Comparative Analysis of Metrics for Anomaly Localization in Medical Images. 138-148 - Lemar Abdi, M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Peter H. N. de With, Fons van der Sommen:
Typicality Excels Likelihood for Unsupervised Out-of-Distribution Detection in Medical Imaging. 149-159 - Harry Anthony, Konstantinos Kamnitsas:
Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection. 160-170 - Franciskus Xaverius Erick, Mina Rezaei, Johanna Paula Müller, Bernhard Kainz:
Uncertainty-Aware Vision Transformers for Medical Image Analysis. 171-180
Uncertainty Modelling and Estimation
- Vincent Blot, Alexandra Lorenzo de Brionne, Ines Sellami, Olivier Trassard, Isabelle Beau, Charlotte Sonigo, Nicolas J.-B. Brunel:
Efficient Precision Control in Object Detection Models for Enhanced and Reliable Ovarian Follicle Counting. 183-193 - Xianze Ai, Zehui Liao, Yong Xia:
GLANCE: Combating Label Noise Using Global and Local Noise Correction for Multi-label Chest X-Ray Classification. 194-204 - Christopher Clark, Scott Kinder, Didem Egemen, Brian Befano, Kanan T. Desai, Syed Rakin Ahmed, Praveer Singh, Ana Cecilia Rodriguez, Jose Jeronimo, Silvia De Sanjosé, Nicolas Wentzensen, Mark Schiffman, Jayashree Kalpathy-Cramer:
Conformal Prediction and Monte Carlo Inference for Addressing Uncertainty in Cervical Cancer Screening. 205-214 - Shelley Zixin Shu, Aurélie Pahud de Mortanges, Alexander Poellinger, Dwarikanath Mahapatra, Mauricio Reyes:
INFORMER- Interpretability Founded Monitoring of Medical Image Deep Learning Models. 215-224
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