Ruisheng Su: Stroke Timer Is an Early Accept at MICCAI 2026
Ruisheng Su, Assistant Professor at Eindhoven University of Technology, shared on LinkedIn:
‘Very happy and proud that our Stroke Timer work, led by our student Weiru Wang, is an early accept (top 9%) at MICCAI 2026 this year.
Paper 549: Stroke Timer: Robust Representation Learning for Ischemic Stroke Onset-Time Estimation from Non-contrast CT
Authors: Weiru Wang, Susan Olthuis, Lisa L., Robert van Oostenbrugge, Charles Majoie, Wim van Zwam, Ruisheng Su
In this work, we propose a fully automatic framework for estimating stroke onset time from non-contrast CT images across three clinically relevant time windows: <4.5 hours, 4.5–6 hours, and >6 hours, without requiring manual lesion delineations.
Stroke onset time is a critical factor in determining appropriate treatment strategies for ischemic stroke.
Stroke Timer addresses this challenge by leveraging self-supervised semantic-style disentanglement and energy-guided contrastive mean-shift for robust representation learning in a long-tail distribution setting.
A special thanks to our collaborators at Maastricht UMC+ (Wim van Zwam, Susan Olthuis, Lisa L.) for their continued involvement and valuable clinical insights throughout this project.
Congratulations to Weiru Wang and all co-authors on this well-recognized work!
More details will follow soon!
Please feel free to reach out if you would like to test out the method or learn more.”
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