Biomedical Optics Express · 2023 · 16 citations · 17 references
Health ProfessionsComputer ScienceOphthalmologyComputer VisionDiagnostic ImagingMachine LearningDiabetic RetinopathyFluorescein AngiographyMedical ImagingOphthalmic ImagingOptical Coherence TomographyRetinal ImagingConvolutional Neural NetworksDiabetic Retinopathy AssessmentDiabetic Retinopathy DetectionFundus Fluorescein AngiographyLeakageRetinal Image ProcessingRetinal Vascular Occlusion ImagingVascular Leakage Detection
Optical coherence tomography angiography (OCTA) covers most functions of fluorescein angiography (FA) when imaging the retina but lacks the ability to depict vascular leakage. Based on OCTA, we developed artificial intelligence-inferred-FA (AI-FA) to delineate leakage in eyes with diabetic retinopathy (DR). Training data of 19,648 still FA images were prepared from FA-photo and videos of 43 DR eyes. AI-FA images were generated using a convolutional neural network. AI-FA images achieved a structural similarity index of 0.91 with corresponding real FA images in DR. The AI-FA generated from OCTA correctly depicted vascular occlusion and associated leakage with enough quality, enabling precise DR diagnosis and treatment planning. A combination of OCT, OCTA, and AI-FA yields more information than real FA with reduced acquisition time without risk of allergic reactions.
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Zhou Wang, Alan C. Bovik, Hamid R. Sheikh et al. · IEEE Transactions on Image Processing · 2004 · 56K citations
Takao Hirano, Jyunya Kitahara, Yuichi Toriyama et al. · British Journal of Ophthalmology · 2018 · 121 citations · Full text