Year: 2025
Type: article
Abstract: Retinal diseases, encompassing a wide spectrum of ocular disorders, pose significant threats to vision and overall eye health. Early and accurate diagnosis is crucial for timely intervention and treatment planning. In recent years, the integration of deep learning techniques into medical imaging has revolutionized the field of ophthalmology. This study explores the application of deep learning algorithms for the classification of retinal diseases using high-resolution retinal images. This study presents a comprehensive and innovative framework for retinal disease classification using deep learning, addressing critical technical challenges and ethical considerations. The developed model represents a significant step towards enhancing the accuracy and efficiency of retinal disease diagnosis, ultimately improving patient outcomes and the quality of eye care.. Keywords : Retinal movement, disease discrimination, deep learning, CNN classifier.
DOI: 10.55041/ijsrem41734
Author: Sayali Shivarkar1
Language: English
Topic: Retinal Imaging and Analysis
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4407808029