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20242026
most citedEnhancing Diagnostic Accuracy in Rare and Common Fundus Diseases with a Knowledge-Rich Vision-Language Model

1 citations · 1 across the 5 of their papers we have counts for

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cs.CV2025

GLCP: Global-to-Local Connectivity Preservation for Tubular Structure Segmentation

Feixiang Zhou, Zhuangzhi Gao, He Zhao +5

Accurate segmentation of tubular structures, such as vascular networks, plays a critical role in various medical domains. A remaining significant challenge in this task is structur…

cs.CV2025

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation

Ming Yin, Fu Wang, Xujiong Ye +2

Surgical video segmentation is a critical task in computer-assisted surgery, essential for enhancing surgical quality and patient outcomes. Recently, the Segment Anything Model 2 (…

cs.CV2025

Robust Incomplete-Modality Alignment for Ophthalmic Disease Grading and Diagnosis via Labeled Optimal Transport

Qinkai Yu, Jianyang Xie, Yitian Zhao +7

Multimodal ophthalmic imaging-based diagnosis integrates color fundus image with optical coherence tomography (OCT) to provide a comprehensive view of ocular pathologies. However,…

cs.CV2025

Parameterized Diffusion Optimization enabled Autoregressive Ordinal Regression for Diabetic Retinopathy Grading

Qinkai Yu, Wei Zhou, Hantao Liu +7

As a long-term complication of diabetes, diabetic retinopathy (DR) progresses slowly, potentially taking years to threaten vision. An accurate and robust evaluation of its severity…

cs.CV2025

Clinician-Friendly Foundation Models for Ophthalmic Image Diagnostics without Fine-Tuning or Technical Barriers

Meng Wang, Tian Lin, Qingshan Hou +69

Artificial intelligence (AI) shows remarkable potential in medical imaging diagnostics, yet most current models require retraining when applied across different clinical settings,…