AIMC Topic: Fluorescein Angiography
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Evaluation of AI-enhanced non-mydriatic fundus photography for diabetic retinopathy screening.
Photodiagnosis and photodynamic therapy
Sep 7, 2024
OBJECTIVE: To assess the feasibility of using non-mydriatic fundus photography in conjunction with an artificial intelligence (AI) reading platform for large-scale screening of diabetic retinopathy (DR).
Artificial intelligence-based extraction of quantitative ultra-widefield fluorescein angiography parameters in retinal vein occlusion.
Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
Aug 31, 2024
OBJECTIVE: To examine the association between quantitative vascular parameters extracted from intravenous fluorescein angiography (IVFA) and baseline clinical characteristics of patients with retinal vein occlusion (RVO).
Prediction of treatment outcome for branch retinal vein occlusion using convolutional neural network-based retinal fluorescein angiography.
Scientific reports
Aug 28, 2024
Deep learning techniques were used in ophthalmology to develop artificial intelligence (AI) models for predicting the short-term effectiveness of anti-VEGF therapy in patients with macular edema secondary to branch retinal vein occlusion (BRVO-ME). 1...
Automated identification of fleck lesions in Stargardt disease using deep learning enhances lesion detection sensitivity and enables morphometric analysis of flecks.
The British journal of ophthalmology
Aug 22, 2024
PURPOSE: To classify fleck lesions and assess artificial intelligence (AI) in identifying flecks in Stargardt disease (STGD).
Linking disease activity with optical coherence tomography angiography in neovascular age related macular degeneration using artificial intelligence.
Scientific reports
Aug 20, 2024
To investigate quantitative associations between AI-assessed disease activity and optical coherence tomography angiography (OCTA)-derived parameters in patients with neovascular age-related macular degeneration (nAMD) undergoing anti-VEGF therapy. OC...
Disease Activity and Therapeutic Response to Pegcetacoplan for Geographic Atrophy Identified by Deep Learning-Based Analysis of OCT.
Ophthalmology
Aug 14, 2024
PURPOSE: To quantify morphological changes of the photoreceptors (PRs) and retinal pigment epithelium (RPE) layers under pegcetacoplan therapy in geographic atrophy (GA) using deep learning-based analysis of OCT images.
Cognitive vision: AI automation of the surgical eye in fluorescence angiography - correspondence.
International journal of surgery (London, England)
Aug 1, 2024
[Use of artificial intelligence in geographic atrophy in age-related macular degeneration].
Die Ophthalmologie
Jul 31, 2024
The first regulatory approval of treatment for geographic atrophy (GA) secondary to age-related macular degeneration in the USA constitutes an important milestone; however, due to the nature of GA as a non-acute, insidiously progressing pathology, th...
[OCT biomarkers in diabetic maculopathy and artificial intelligence].
Die Ophthalmologie
Jul 16, 2024
Diabetes mellitus is a chronic disease the microvascular complications of which include diabetic retinopathy and maculopathy. Diabetic macular edema, proliferative diabetic retinopathy, and diabetic macular ischemia pose a threat to visual acuity. Ar...
Protocol for performing deep learning-based fundus fluorescein angiography image analysis with classification and segmentation tasks.
STAR protocols
Jun 19, 2024
Fundus fluorescein angiography (FFA) examinations are widely used in the evaluation of fundus disease conditions to facilitate further treatment suggestions. Here, we present a protocol for performing deep learning-based FFA image analytics with clas...
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