works on

From the 1 of 11 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 4 of their papers we have counts for

collaborators

11 papers

cs.CV2026

BrainNext: A General-Purpose Self-Supervised Foundation Model for Brain MRI Analysis

Moona Mazher, Abdul Qayyum, Steven A. Niederer +1

Foundation models pretrained using self-supervised learning have transformed computer vision by learning transferable representations from large-scale unlabeled data. However, exis…

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…

cs.CV2026

Towards Brain MRI Foundation Models for the Clinic: Findings from the FOMO25 Challenge

Asbjørn Munk, Stefano Cerri, Vardan Nersesjan +81

Clinical deployment of automated brain MRI analysis faces a fundamental challenge: clinical data is heterogeneous and noisy, and high-quality labels are prohibitively costly to obt…

cs.CV2026

TriALS: Triphasic-Aided Liver Lesion Segmentation Benchmark in Non-Contrast CT

Marawan Elbatel, Mohamed Ghonim, Jiaji Mao +62

Automated segmentation of liver lesions on non-contrast computed tomography (NCCT) is clinically important but fundamentally challenging, particularly in low-resource settings acro…

eess.IV2026

SegRap2025: A Benchmark of Gross Tumor Volume and Lymph Node Clinical Target Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma

Jia Fu, Litingyu Wang, He Li +27

Accurate delineation of Gross Tumor Volume (GTV), Lymph Node Clinical Target Volume (LN CTV), and Organ-at-Risk (OAR) from Computed Tomography (CT) scans is essential for precise r…

cs.CV2025

Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challenge

Rachid Zeghlache, Ikram Brahim, Pierre-Henri Conze +47

The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) through the analysis of optical cohe…