9 citations · 18 across the 5 of their papers we have counts for
6 papers
Synthetic Melanoma Image Generation and Evaluation Using Generative Adversarial Networks
Pei-Yu Lin, Yidan Shen, Neville Mathew +6
Melanoma is the most lethal form of skin cancer, and early detection is critical for improving patient outcomes. Although dermoscopy combined with deep learning has advanced automa…
EyeAgent: An Agentic AI System for Multimodal Clinical Decision Support in Ophthalmology
Danli Shi, Xiaolan Chen, Bingjie Yan +24
Artificial intelligence has shown promise in medical imaging, yet most existing systems lack flexibility, interpretability, and adaptability - challenges especially pronounced in o…
Fundus to Fluorescein Angiography Video Generation as a Retinal Generative Foundation Model
Weiyi Zhang, Jiancheng Yang, Ruoyu Chen +7
Fundus fluorescein angiography (FFA) is crucial for diagnosing and monitoring retinal vascular issues but is limited by its invasive nature and restricted accessibility compared to…
EyeCLIP: A visual-language foundation model for multi-modal ophthalmic image analysis
Danli Shi, Weiyi Zhang, Jiancheng Yang +8
Early detection of eye diseases like glaucoma, macular degeneration, and diabetic retinopathy is crucial for preventing vision loss. While artificial intelligence (AI) foundation m…
Fundus2Video: Cross-Modal Angiography Video Generation from Static Fundus Photography with Clinical Knowledge Guidance
Weiyi Zhang, Siyu Huang, Jiancheng Yang +5
Fundus Fluorescein Angiography (FFA) is a critical tool for assessing retinal vascular dynamics and aiding in the diagnosis of eye diseases. However, its invasive nature and less a…
EyeFound: A Multimodal Generalist Foundation Model for Ophthalmic Imaging
Danli Shi, Weiyi Zhang, Xiaolan Chen +6
Artificial intelligence (AI) is vital in ophthalmology, tackling tasks like diagnosis, classification, and visual question answering (VQA). However, existing AI models in this doma…