Retinal Diseases Classification using Deep Learning

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.

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-02-21
DOI
https://doi.org/10.55041/ijsrem41734
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Retinal Diseases Classification using Deep Learning

Sayali Shivarkar
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Retinal Imaging and Analysis
article

Retinal Diseases Classification using Deep Learning

Sayali Shivarkar
article en

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.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(02)
Openalex Percentile: Top 95%
Retinal Imaging and Analysis
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