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researcher

M. Mossa-Basha

3 papers hereh-index 8698 citations90 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV3

identity via Semantic Scholar / OpenAlex

works on
angiography 1benchmark challenge 1circle of willis segmentation 1deep learning 1vascular imaging 1

From the 1 of 3 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 1 of their papers we have counts for

collaborators

3 papers

cs.CV2026★ 12 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

Unified and Semantically Grounded Domain Adaptation for Medical Image Segmentation

Xin Wang, Yin Guo, Jiamin Xia +5

Most prior unsupervised domain adaptation approaches for medical image segmentation are narrowly tailored to either the source-accessible setting, where adaptation is guided by sou…

cs.CV2025

RemInD: Remembering Anatomical Variations for Interpretable Domain Adaptive Medical Image Segmentation

Xin Wang, Yin Guo, Kaiyu Zhang +4

This work presents a novel Bayesian framework for unsupervised domain adaptation (UDA) in medical image segmentation. While prior works have explored this clinically significant ta…

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