akshitadixit/Retinopathy
This is a Categorical Detection and Prediction Task based on subset of a Kaggle dataset from Eye Images (Aravind Eye hospital) - APTOS 2019 Challenge. The goal is to predict the Blindness Stage (0-4) class from the Eye retina Image using Deep Learning Models (transfer learning via resnet50). This Automated System would speed up Blindness detection on Patients. Work in progress.
This project helps ophthalmologists and eye care professionals quickly assess fundus photography images for signs of diabetic retinopathy. It takes an eye retina image as input and outputs a prediction of the blindness stage, on a scale of 0 (No DR) to 4 (Proliferative DR). This automated system aims to speed up the detection of diabetic retinopathy in patients.
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Use this if you need an automated tool to classify the severity of diabetic retinopathy from fundus images, aiding in faster patient screening and diagnosis.
Not ideal if you require a diagnostic tool that accounts for significant image noise, focus issues, or varying exposure without prior image quality control.
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Jun 04, 2021
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