arXiv:2609.15550v1 Announce Type: cross
Abstract: X-ray coronary angiography is the clinical gold standard for coronary artery disease during real-time cardiac interventions, but provides only 2D pro...
By Deyu Meng, Mojtaba Lashgari, Yiying Wang, Abhirup Banerjee
arXiv:2609.15400v1 Announce Type: new
Abstract: Vessel segmentation in X-ray coronary angiography (XCA) is a fundamental step for quantitative coronary analysis and subsequent assessment of coronary...
By Wanxian Li, Jiaqian Qin, Qingyi Xian, Yazhi Li, Song Chen, Liman Li, Hao He
arXiv:2608.24783v1 Announce Type: new
Abstract: Accurate segmentation of coronary arteries in X-ray angiography videos is essential for quantitative coronary analysis and image-guided interventions....
By Lin Xi, Yingliang Ma
arXiv:2606. 16234v1 Announce Type: cross Abstract: Fundus fluorescein angiography (FFA) is critical for assessing retinal vascular abnormalities, but its acquisition is invasive and not always feasible.
By Tengfei Ma, Ruiqi Wu, Chenran Zhang, Ye Geng, Na Su, Xiangyuan Duanmu, Tao Zhou, Yi Zhou, Wen Fan
arXiv:2606. 05375v1 Announce Type: cross Abstract: Optical coherence tomographic angiography (OCTA) is a powerful technique for imaging retinal microvasculature.
By Yukun Guo, Min Gao, Tristan T. Hormel, Steven T. Bailey, Thomas S. Hwang, Yali Jia
X‑LMC is a spatiotemporal deep‑learning framework that automatically scores leptomeningeal collateral (LMC) status from time‑resolved biplane digital subtraction angiography (DSA). It uses a DINOv2 backbone to encode spatial frames, a token‑level cross‑view attention module to fuse orthogonal projections, and a recurrent network to model contrast bolus dynamics. On a multicenter dataset of 134 M1‑segment occlusion patients, X‑LMC achieved a Quadratic Weighted Kappa of 0.398 and a macro‑F1 of 0.711, outperforming static and other spatiotemporal baselines and matching clinical inter‑rater agreement.