Work

Development of an OCT image analysis algorithm for differential diagnosis of retinal edema based on deep learning

Year: 2025

Type: article

Abstract: The aim of this work is to develop an algorithm for differential diagnosis of retinal edema and study deep learning methods and their application to image analysis. The application of convolutional neural networks for the task of semantic segmentation of retinal layers is investigated and its efficiency is proved for two selected layers (pigment epithelium and retina). An algorithm of disease classification based on the intellectual analysis of the layers selected by the neural network is implemented. A proof of its applicability for differential diagnostics of retinal edema is presented. The accuracy of disease detection amounts to 90%.

Source: Computer Optics

DOI: 10.18287/2412-6179-co-1613

Authors: N.S. Demin, N.Y. Ilyasova, E.A. Zamytskiy, A.V. Zolotarev, D.V. Kirsh, A.Y. Ionov

Institutions: Kurchatov Institute, Samara National Research University, Image Processing Systems Institute, Samara State Medical University

Language: English

Topic: Retinal Imaging and Analysis

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4412006789