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ORCIDUNSURE@MICCAI 2025: Daejeon, South Korea
- Carole H. Sudre
, Mobarak I. Hoque, Raghav Mehta, Cheng Ouyang, Chen Qin, Marianne Rakic, William M. Wells:
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging - 7th International Workshop, UNSURE 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings. Lecture Notes in Computer Science 16166, Springer 2026, ISBN 978-3-032-06592-6
Risk management, Uncertainty Interpretation and Visualisation
- Damola Agbelese, Krishna Chaitanya, Pushpak Pati, Chaitanya Parmar, Pooya Mobadersany, Shreyas Fadnavis, Lindsey Surace, Shadi Yarandi, Louis Ghanem, Molly V. Lucas, Tommaso Mansi, Gabriela Oana Cula, Pablo F. Damasceno, Kristopher Standish:
MEGAN: Mixture of Experts for Robust Uncertainty Estimation in Endoscopy Videos. 3-13 - Levente Lippenszky, Hongxu Yang, José de Arcos, László Ruskó:
Unsupervised Artifact Detection and Quantification via Contrastive Learning with Noise Reference. 14-23 - Matthias Schwab, Markus Haltmeier, Agnes Mayr:
Disagreement-Driven Uncertainty Quantification in Late Gadolinium Enhancement Cardiac MRI. 24-33 - Anna M. Wundram, Christian F. Baumgartner:
Is Uncertainty Quantification a Viable Alternative to Learned Deferral? 34-44 - Gabriel Oliveira-Stahl, Anna Schroder, James Moggridge, Hamza A. Salhab, Caroline Micallef, Josephine Barnes, M. Jorge Cardoso, Carole H. Sudre, Matthew Grech-Sollars:
Evaluation of Uncertainty-Aware Multi-software Ensembles for Hippocampal Segmentation. 45-55 - Niusha Mirhakimi, Yohan Chatelain, Jean-Baptiste Poline, Tristan Glatard:
Numerical Uncertainty in Linear Registration: An Experimental Study. 56-66
Domain Shift and Out-of-Distribution Management
- Asif Hanif, Zaigham Zaheer, Salman Khan, Fahad Shahbaz Khan, Rao Muhammad Anwer:
SPARTA: Spectral Prompt Agnostic Adversarial Attack on Medical Vision-Language Models. 69-80 - Tim Flühmann, Alceu Bissoto, Trung-Dung Hoang, Lisa M. Koch:
Label-Free Estimation of Clinically Relevant Performance Metrics Under Distribution Shifts. 81-90 - Lemar Abdi, Francisco Caetano, M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Hamdi Joudeh, Fons van der Sommen:
Out-of-Distribution Detection in Medical Imaging via Diffusion Trajectories. 91-101 - Jeongun Ryu, Heon Song, Seungeun Lee, Soo Ick Cho, Jiwon Shin, Kyunghyun Paeng, Sérgio Pereira:
SCORPION: Addressing Scanner-Induced Variability in Histopathology. 102-111 - Kudaibergen Abutalip, Numan Saeed, Fadillah A. Maani, Ikboljon Sobirov, Vincent Andrearczyk, Adrien Depeursinge, Mohammad Yaqub:
LEXU: Learning from Expert Disagreement for Single-Pass Uncertainty Estimation in Medical Image Segmentation. 112-122 - Umaima Rahman, Raza Imam, Mohammad Yaqub, Dwarikanath Mahapatra:
Decoupling Clinical and Class-Agnostic Features for Reliable Few-Shot Adaptation Under Shift. 123-133 - Van Phi Nguyen, Ngoc Huynh Trinh, Duy Minh Lam Nguyen, Phu Loc Nguyen, Quoc Long Tran:
Aleatoric Uncertainty Medical Image Segmentation Estimation via Flow Matching. 134-144
Uncertainty Calibration
- Meritxell Riera-Marin, Javier García López, Júlia Rodríguez-Comas, Miguel Ángel González Ballester, Adrian Galdran:
Multi-Rater Calibration Error Estimation. 147-157 - Ang Nan Gu, Michael Y. Tsang, Hooman Vaseli, Purang Abolmaesumi, Teresa Tsang:
Pseudo-D: Informing Multi-view Uncertainty Estimation with Calibrated Neural Training Dynamics. 158-168 - Matt Y. Cheung, Tucker J. Netherton, Laurence E. Court, Ashok Veeraraghavan, Guha Balakrishnan:
Metric-Guided Conformal Bounds for Probabilistic Image Reconstruction. 169-179 - Gonzalo Esteban Mosquera Rojas, Sebastian R. van der Voort, Carolin M. Pirkl, Sandeep Kaushik, Marion Smits, Stefan Klein:
Evaluation of Monte Carlo Dropout for Uncertainty Quantification in Multi-task Deep Learning-Based Glioma Subtyping. 180-190
Uncertainty Modelling and Estimation, Bayesian Deep Learning
- Simon Baur, Wojciech Samek, Jackie Ma:
Benchmarking Uncertainty and Its Disentanglement in Multi-label Chest X-Ray Classification. 193-203 - Peter Johannes Tejlgaard Kampen, Marcel Reimann, Morten Rieger Hannemose, Anders Nymark Christensen, Miriam Kolko, Anders Bjorholm Dahl, Josefine Vilsbøll Sundgaard:
Uncertainty-Aware Classification: A Human-Guided Bayesian Deep Learning Framework. 204-213 - Kevin Raina:
Empirical Bayesian Methods and BNNs for Medical OOD Detection. 214-223 - Disi Lin, Anders Garpebring, Tommy Löfstedt:
A Proper Structured Prior for Bayesian T1 Mapping. 224-233 - Teo Deveney, Ivor Simpson, Neill D. F. Campbell:
Bayesian MRI Reconstruction with Structured Uncertainty Distributions. 234-243
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