9 citations · 28 across the 19 of their papers we have counts for
11 papers · 1 filter
FFA Sora, video generation as fundus fluorescein angiography simulator
Xinyuan Wu, Lili Wang, Ruoyu Chen +6
Fundus fluorescein angiography (FFA) is critical for diagnosing retinal vascular diseases, but beginners often struggle with image interpretation. This study develops FFA Sora, a t…
Visual Question Answering in Ophthalmology: A Progressive and Practical Perspective
Xiaolan Chen, Ruoyu Chen, Pusheng Xu +4
Accurate diagnosis of ophthalmic diseases relies heavily on the interpretation of multimodal ophthalmic images, a process often time-consuming and expertise-dependent. Visual Quest…
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…
UWF-RI2FA: Generating Multi-frame Ultrawide-field Fluorescein Angiography from Ultrawide-field Retinal Imaging Improves Diabetic Retinopathy Stratification
Ruoyu Chen, Kezheng Xu, Kangyan Zheng +4
Ultrawide-field fluorescein angiography (UWF-FA) facilitates diabetic retinopathy (DR) detection by providing a clear visualization of peripheral retinal lesions. However, the intr…
Hypergraph Multi-modal Large Language Model: Exploiting EEG and Eye-tracking Modalities to Evaluate Heterogeneous Responses for Video Understanding
Minghui Wu, Chenxu Zhao, Anyang Su +8
Understanding of video creativity and content often varies among individuals, with differences in focal points and cognitive levels across different ages, experiences, and genders.…
Choroidal Vessel Segmentation on Indocyanine Green Angiography Images via Human-in-the-Loop Labeling
Ruoyu Chen, Ziwei Zhao, Mayinuer Yusufu +3
Human-in-the-loop (HITL) strategy has been recently introduced into the field of medical image processing. Indocyanine green angiography (ICGA) stands as a well-established examina…
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…
Evaluating large language models in medical applications: a survey
Xiaolan Chen, Jiayang Xiang, Shanfu Lu +3
Large language models (LLMs) have emerged as powerful tools with transformative potential across numerous domains, including healthcare and medicine. In the medical domain, LLMs ho…
EyeGPT: Ophthalmic Assistant with Large Language Models
Xiaolan Chen, Ziwei Zhao, Weiyi Zhang +7
Artificial intelligence (AI) has gained significant attention in healthcare consultation due to its potential to improve clinical workflow and enhance medical communication. Howeve…