To establish a multimodal fundus image report generation model to realize an interpretable system for multiple fundus diseases, multimodal image analysis, diagnosis, and treatment decision automatic reporting based on weakly labeled training data. Construct an interpretable feature fusion network for the clinical and imaging features of fundus lesions, and we hope to extract new imaging markers that can predict the occurrence and progression of various fundus lesions at an early stage, and ultimately verify them in real clinical data, further providing possible directions for exploring the molecular mechanisms of refractory fundus lesions, and may also provide new ideas for the precise prevention and treatment of fundus lesions.
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Fundus Fluorescein Angiography (FFA) images with corresponding report
Timeframe: Baseline
Indocyanine Green Angiography (ICGA) images with report
Timeframe: Baseline
Fundus photography with corresponding report
Timeframe: Baseline
Optical coherence tomography (OCT) images with corresponding report
Timeframe: Baseline
Optical coherence tomography angiography (OCTA) images with corresponding report
Timeframe: Baseline