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Fundus image based diagnosis and clinical decision support system for early prediction of glaucoma and grading of diabetic retinopathies

Project Overview

Image-based diagnosis and clinical decision support system is proposed for two very severe ophthalmic diseases glaucoma and diabetic retinopathies DR. Fundus images have very fine blood cells hence it is a challenge to differentiate between healthy and malignant images.

Benefits

Their proposed method will be beneficial in automatic early screening of diseases and prevent blindness. It will not only detect glaucoma and four stages of DR but
also reduce examination time and manual errors. The model efficiency will be tested on benchmarks fundus image datasets, ACRIMA, Drishti-GSI, Kaggle and Messidor datasets.
Funding Organization
Quick Information
Thrust Areas
Medical Sciences
Focus Area
Medical Device, Digital Health
Status
Proof of Concept
Source Title
Data sourced from Biotechnology Industry Research Assistance Council (BIRAC), Department of Biotechnology (DBT)
Output
Status
Proof of Concept
TRL: Technology Readiness Level
TRL-2
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