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From the 1 of 5 linked papers with an AI index.

most citedThe TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

12 citations · 12 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV202612 cited

The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

Kaiyuan Yang, Fabio Musio, Yihui Ma +112

The paper introduces the TopCoW Challenge, a benchmark for automatically segmenting the Circle of Willis in CT and MR angiography using deep learning, and provides a new annotated…

eess.IV2026

Explainability in mulimodal deep transformation models for stroke outcome prediction

Lisa Herzog, Jonas Brändli, Maurice Schneeberger +7

Multimodal prediction models based on imaging and clinical data are increasingly used for clinical decision support, yet their interpretability remains limited. We present multimod…

eess.IV2026

Leptomeningeal Collateral Detection on DSA via Vessel-Graph Neural Networks

Junyong Cao, Hakim Baazaoui, Chinmay Prabhakar +5

Leptomeningeal collaterals (LMCs) are an important prognostic factor in acute ischemic stroke. Existing automated methods rely on CT angiography (CTA), but individual LMCs are ofte…

eess.IV2025

ISLES'24: Final Infarct Prediction with Multimodal Imaging and Clinical Data. Where Do We Stand?

Ezequiel de la Rosa, Ruisheng Su, Mauricio Reyes +37

Accurate estimation of brain infarction (i.e., irreversibly damaged tissue) is critical for guiding treatment decisions in acute ischemic stroke. Reliable infarct prediction inform…

cs.CV2025

ISLES'24 -- A Real-World Longitudinal Multimodal Stroke Dataset

Evamaria Olga Riedel, Ezequiel de la Rosa, The Anh Baran +18

Stroke remains a leading cause of global morbidity and mortality, imposing a heavy socioeconomic burden. Advances in endovascular reperfusion therapy and CT and MR imaging for trea…