angiography 1arrhythmogenic cardiomyopathy 1benchmark challenge 1boundary value problems 1cardiac imaging 1circle of willis segmentation 1deep learning 1endometriosis subtyping 1kinetic theory 1machine learning 1multimodal data 1multi-scale features 1
From the 4 of 36 papers with an AI index.
50 citations
- IMT AtlantiqueFR11 papers
- Laboratoire de Physique Subatomique et des Technologies AssociéesFR10 papers
- Laboratoire des Sciences du Numérique de NantesFR10 papers
- Centre National de la Recherche ScientifiqueFR9 papers
- Le Mans UniversitéFR5 papers
- Laboratoire de Mathématiques Jean LerayFR4 papers
- Centre de physique des particules de MarseilleFR3 papers
- École Centrale de NantesFR3 papers
- École Nationale Supérieure d'Ingénieurs de CaenFR3 papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR3 papers
- Institut Pluridisciplinaire Hubert CurienFR3 papers
- Laboratoire de Physique Corpusculaire de CaenFR3 papers
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cs.CV2026
A novel unsupervised machine learning strategy to handle multimodal cardiac PET/MRI data
Brunnhilde Ponsi, Thomas Carlier, Lara Marteau +5
The paper presents an unsupervised clustering pipeline that integrates PET and MRI cardiac images to automatically detect abnormal myocardial regions in patients with arrhythmogeni…
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…