Artificial intelligence in retinal disease: clinical application, challenges, and future directions
Retinal diseases are a leading cause of blindness in developed countries, accounting for
the largest share of visually impaired children, working-age adults (inherited retinal …
the largest share of visually impaired children, working-age adults (inherited retinal …
Automated retinal layer segmentation using graph-based algorithm incorporating deep-learning-derived information
Z Mishra, A Ganegoda, J Selicha, Z Wang… - Scientific Reports, 2020 - nature.com
Regular drusen, an accumulation of material below the retinal pigment epithelium (RPE),
have long been established as a hallmark early feature of nonneovascular age-related …
have long been established as a hallmark early feature of nonneovascular age-related …
[HTML][HTML] Artificial intelligence for assessment of Stargardt macular atrophy
Stargardt disease (also known as juvenile macular degeneration or Stargardt macular
degeneration) is an inherited disorder of the retina, which can occur in the eyes of children …
degeneration) is an inherited disorder of the retina, which can occur in the eyes of children …
Deep learning-based classification of inherited retinal diseases using fundus autofluorescence
A Miere, T Le Meur, K Bitton, C Pallone… - Journal of Clinical …, 2020 - mdpi.com
Background. In recent years, deep learning has been increasingly applied to a vast array of
ophthalmological diseases. Inherited retinal diseases (IRD) are rare genetic conditions with …
ophthalmological diseases. Inherited retinal diseases (IRD) are rare genetic conditions with …
Detection of retinal abnormalities in fundus image using CNN deep learning networks
Abstract The World Health Organization (WHO) estimates that 285 million people are
visually impaired worldwide, with 39 million blinds. Glaucoma, cataract, age-related macular …
visually impaired worldwide, with 39 million blinds. Glaucoma, cataract, age-related macular …
Deep learning-based classification of retinal atrophy using fundus autofluorescence imaging
A Miere, V Capuano, A Kessler, O Zambrowski… - Computers in Biology …, 2021 - Elsevier
Purpose To automatically classify retinal atrophy according to its etiology, using fundus
autofluorescence (FAF) images, using a deep learning model. Methods In this study, FAF …
autofluorescence (FAF) images, using a deep learning model. Methods In this study, FAF …
Automated segmentation and feature discovery of age-related macular degeneration and Stargardt disease via self-attended neural networks
Age-related macular degeneration (AMD) and Stargardt disease are the leading causes of
blindness for the elderly and young adults respectively. Geographic atrophy (GA) of AMD …
blindness for the elderly and young adults respectively. Geographic atrophy (GA) of AMD …
Using Ensemble OCT-Derived Features beyond Intensity Features for Enhanced Stargardt Atrophy Prediction with Deep Learning
Featured Application This study shows promising results for the development of artificial
intelligence tools for the predicting of the progression of Stargardt disease. It further offers …
intelligence tools for the predicting of the progression of Stargardt disease. It further offers …
[HTML][HTML] Recurrent and concurrent prediction of longitudinal progression of stargardt atrophy and geographic atrophy towards comparative performance on optical …
Z Mishra, ZC Wang, E Xu, S Xu, I Majid, SVR Sadda… - Applied Sciences, 2024 - mdpi.com
Stargardt atrophy and geographic atrophy (GA) represent pivotal endpoints in FDA-
approved clinical trials. Predicting atrophy progression is crucial for evaluating drug efficacy …
approved clinical trials. Predicting atrophy progression is crucial for evaluating drug efficacy …
Reverse engineering for reconstructing baseline features of dry age-related macular degeneration in optical coherence tomography
Age-related macular degeneration (AMD) is the most widespread cause of blindness and
the identification of baseline AMD features or biomarkers is critical for early intervention …
the identification of baseline AMD features or biomarkers is critical for early intervention …