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From the 1 of 12 linked papers with an AI index.

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20242026
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

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Showing eess.IVShow all

6 papers · 1 filter

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

CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography

Murong Xu, Tamaz Amiranashvili, Fernando Navarro +30

Accurate delineation of anatomical structures in volumetric CT scans is crucial for diagnosis and treatment planning. While AI has advanced automated segmentation, current approach…

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…

eess.IV2025

Outcome prediction and individualized treatment effect estimation in patients with large vessel occlusion stroke

Lisa Herzog, Pascal Bühler, Ezequiel de la Rosa +2

Mechanical thrombectomy has become the standard of care in patients with stroke due to large vessel occlusion (LVO). However, only 50% of successfully treated patients show a favor…

eess.IV2025

BraTS orchestrator : Democratizing and Disseminating state-of-the-art brain tumor image analysis

Florian Kofler, Marcel Rosier, Mehdi Astaraki +34

The Brain Tumor Segmentation (BraTS) cluster of challenges has significantly advanced brain tumor image analysis by providing large, curated datasets and addressing clinically rele…

eess.IV2024

Efficient MedSAMs: Segment Anything in Medical Images on Laptop

Jun Ma, Feifei Li, Sumin Kim +79

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive co…