2 papers
cs.CV2026
Enabling Vision and Cross-Modal Learning for Multimodal Stroke Recurrence Prediction: An Interpretable Two-Step Framework
Christian Gapp, Elias Tappeiner, Martin Welk +8
Multimodal stroke recurrence prediction requires effective integration of heterogeneous clinical and imaging data, yet modality imbalance often causes models to over-rely on domina…
eess.IV2025
Semi-supervised learning and integration of multi-sequence MR-images for carotid vessel wall and plaque segmentation
Marie-Christine Pali, Christina Schwaiger, Malik Galijasevic +3
The analysis of carotid arteries, particularly plaques, in multi-sequence Magnetic Resonance Imaging (MRI) data is crucial for assessing the risk of atherosclerosis and ischemic st…