Article

Interpretable Detection of Epiretinal Membrane from Optical Coherence Tomography with Deep Neural Networks

2022-11-29

Abstract excerpt

<h4>Purpose</h4> To automatically detect epiretinal membranes (ERMs) of different sizes in various OCT scans of the central and paracentral macula region and classify them by size using deep neural networks (DNNs). <h4>Methods</h4> 11,061 OCT-images of 624 volume OCT scans (624 eyes of 461 patients) were included and graded according to the presence of an ERM and its size (small 100-1000µm, large >1000 µm). The da...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: a03743da-f8bc-578e-b6a0-a3fc479e6a5c
DOI: 10.1101/2022.11.24.22282667

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Interpretable Detection of Epiretinal Membrane from Optical Coherence Tomography with Deep Neural NetworksDOI 10.1101/2022.11.24.22282667Read

Clinically Interpretable Deep Learning via Sparse BagNets for Epiretinal Membrane and Related Pathology DetectionSemantic proximity Read

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning.Semantic proximity Read

Self-supervised contrastive learning improves machine learning discrimination of full thickness macular holes from epiretinal membranes in retinal OCT scansSemantic proximity Read

Deep Learning-Based Detection of Reticular Pseudodrusen in Age-Related Macular Degeneration on Optical Coherence TomographySemantic proximity Read

Eye Disease Classification from OCT ImagesSemantic proximity Read

Delineating retinal breaks in ultra-widefield fundus images with a PraNet-based machine learning modelSemantic proximity Read

Automated Detection of Nine Infantile Fundus Diseases and Conditions in Retinal Images Using a Deep Learning SystemSemantic proximity Read

Applications of Artificial Intelligence in Optometric Diagnostics: A Review of Techniques and Clinical ImpactSemantic proximity Read

A Tutorial on Automated Classification of Eye Diseases Using Deep LearningSemantic proximity Read

EDNet-20: Enhancing Multi-Label Ocular Disease Detection through Deep Learning OptimizationSemantic proximity Read

Deep Learning based retinal layer segmentation in optical coherence tomography scans of patients with inherited retinal diseasesSemantic proximity Read

Deriving OCT-Equivalent Retinal Nerve Fiber Layer Thickness Maps from Fundus Photographs with Deep Learning Improves Glaucoma DiagnosisSemantic proximity Read