Hybrid Graph Representation Learning for Carotid Artery Stenosis Detection Based on Multimodal Retinal OCTA Images

• Published in: IEEE access Vol. 13; pp. 9538 - 9548
• Main Authors: Lan, Wenting, Hao, Jinkui, Zhou, Shengjun, Zhang, Jingfeng, Ma, Shaodong, Zhao, Yitian
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Abnormalities; Arteries; Biomarkers; Carotid arteries; Carotid artery stenosis; Deep learning; Diseases; Feature extraction; GNN; Graph representations; Graphical representations; Image analysis; Image resolution; Imaging techniques; Ischemia; Medical imaging; multi-modal; Multimodal sensors; Representation learning; Retina; retinal image; Retinal images; Semantics; Stroke; Stroke (medical condition); Veins; Veins & arteries
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3412961

Carotid artery stenosis (CAS) is one of the major causes of cerebral ischemic stroke. Rapid and precise detection of CAS is crucial for early intervention and reducing ischemic stroke incidence. Neuroimaging techniques, as the gold standard for evaluating cerebral abnormalities in CAS, suffer from l...