Author
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Author 1
Irshad Khalil
Department of Health Science and Technology, Gachon Advanced Institute for Health Sciences and Technology GAIHST, Gachon University, Incheon 21936, Korea
Summary
Edited Journals
IECE Contributions

Free Access | Research Article | 29 October 2024
Enhancing Ocular Health Precision: Cataract Detection Using Fundus Images and ResNet-50
IECE Transactions on Intelligent Systematics | Volume 1, Issue 3: 134-149, 2024 | DOI:10.62762/TIS.2024.640345
Abstract
Cataracts are a leading cause of blindness in Pakistan, contributing to more than 54% of cases due to poor living condition, nutritional deficiencies, and limited healthcare access. Early detection is critical to avoid invasive treatments,but current diagnostic approaches often identify cataracts at advanced stages. This paper presents an advanced,automated cataract detection system using deep learning specifically the ResNet-50 architecture, to address this gap. The model processes fundus retinal images curated from diverse datasets, classified by ophthalmologic experts through a rigorous three-stage process. By leveraging the ResNet-50 model, cataracts are categorized into normal,moderate,... More >

Graphical Abstract
Enhancing Ocular Health Precision: Cataract Detection Using Fundus Images and ResNet-50