AIMC Topic: Stargardt Disease

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A deep learning model for diagnosis of inherited retinal diseases.

Scientific reports Jul 2, 2025
To evaluate the performance of a multi-input deep learning (DL) model in detecting two common inherited retinal diseases (IRDs), i.e. retinitis pigmentosa (RP) and Stargardt disease (STGD), and differentiating them from healthy eyes. This cross-secti...
Adult Cross-Sectional Studies Male Neural Networks, Computer Female Retinal Diseases Stargardt Disease Retinitis Pigmentosa Middle Aged Deep Learning Humans
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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).
Humans Retrospective Studies Female Tomography, Optical Coherence Middle Aged Stargardt Disease Fundus Oculi Fluorescein Angiography Adult Deep Learning Male
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Metabolomics facilitates differential diagnosis in common inherited retinal degenerations by exploring their profiles of serum metabolites.

Nature communications Apr 26, 2024
The diagnosis of inherited retinal degeneration (IRD) is challenging owing to its phenotypic and genotypic complexity. Clinical information is important before a genetic diagnosis is made. Metabolomics studies the entire picture of bioproducts, which...
Macular Degeneration Stargardt Disease Retinitis Pigmentosa Metabolome Diagnosis, Differential Retinal Degeneration Cone-Rod Dystrophies Middle Aged Adolescent Mass Spectrometry Metabolomics Child Adult Male Female Young Adult Machine Learning Biomarkers Humans
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Retinal Boundary Segmentation in Stargardt Disease Optical Coherence Tomography Images Using Automated Deep Learning.

Translational vision science & technology Oct 13, 2020
PURPOSE: To use a deep learning model to develop a fully automated method (fully semantic network and graph search [FS-GS]) of retinal segmentation for optical coherence tomography (OCT) images from patients with Stargardt disease.
Humans Deep Learning Retina Retinal Pigment Epithelium Tomography, Optical Coherence Stargardt Disease
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Automated classification of normal and Stargardt disease optical coherence tomography images using deep learning.

Acta ophthalmologica Jan 24, 2020
PURPOSE: Recent advances in deep learning have seen an increase in its application to automated image analysis in ophthalmology for conditions with a high prevalence. We wanted to identify whether deep learning could be used for the automated classif...
Female Tomography, Optical Coherence Adult Stargardt Disease ROC Curve Severity of Illness Index Humans Male Image Processing, Computer-Assisted Case-Control Studies Middle Aged Deep Learning
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Automatic Cone Photoreceptor Localisation in Healthy and Stargardt Afflicted Retinas Using Deep Learning.

Scientific reports May 21, 2018
We present a robust deep learning framework for the automatic localisation of cone photoreceptor cells in Adaptive Optics Scanning Light Ophthalmoscope (AOSLO) split-detection images. Monitoring cone photoreceptors with AOSLO imaging grants an excell...
Stargardt Disease Deep Learning Macular Degeneration Visual Acuity Algorithms Retina Humans Retinal Cone Photoreceptor Cells Case-Control Studies Neural Networks, Computer
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Automatic Segmentation in Multiple OCT Layers For Stargardt Disease Characterization Via Deep Learning.

Translational vision science & technology Apr 1, 2021
PURPOSE: This study sought to perform automated segmentation of 11 retinal layers and Stargardt-associated features on spectral-domain optical coherence tomography (SD-OCT) images and to analyze differences between normal eyes and eyes diagnosed with...
Retina Algorithms Stargardt Disease Humans Deep Learning Tomography, Optical Coherence
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