Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

deepakpatnaik2002/RetinoAI-Advanced-Diabetic-Retinopathy-Staging

Domain:

healthcare

Record type:

project
Creator:
dee
Host:
This B.Tech project, conducted at ANDHRA UNIVERSITY COLLEGE OF ENGINEERING under the guidance of PROF. SHASHI MOGALLA, with teammates ALOKAM GNANESWARA SAI and BETHA MADHURI, utilizes deep learning techniques to classify Diabetic Retinopathy stages into five types based on eye images. # RetinoAI: Advanced Diabetic Retinopathy Staging - A Deep Learning Method for Classifying Diabetic Retinopathy Stages ## Abstract Diabetic retinopathy, a serious complication of diabetes that can lead to blindness if untreated, affects the retina's blood vessels and may have no early symptoms. Regular comprehensive dilated eye exams are crucial for early detection and treatment. However, accurate stage identification often requires expert analysis of fundus images, which is challenging and costly. To address this, we propose a deep learning-based method using convolutional neural networks (CNNs) for automatic diabetic retinopathy stage detection from single fundus photographs. Our approach also incorporates a multistage transfer learning technique to leverage similar datasets with varied labeling, offering a cost-effective screening solution for early detection. ## Understanding Diabetic Retinopathy: A Medical Overview For a slight introduction to Diabetic Retinopathy, please refer to the document titled **"Diabetic Retinopathy: Medical Overview"**. Diabetic Retinopathy progresses in 4 stages: 1. Mild non-proliferative retinopathy: the earliest stage, where only microaneurysms can occur. 2. Moderate non-proliferative retinopathy: a stage which can be described by losing the blood vessels’ ability of blood transportation due to their distortion and swelling with the progress of the Disease. 3. Severe non-proliferative retinopathy: results in deprived blood supply to the retina due to the increased blockage of more blood vessels, hence signaling the retina for the growing of fresh blood vessels; 4. Proliferative diabetic retinopathy: It is the advanced stage, where the growth features secreted by the retina activate proliferation of the new blood vessels, growing along inside covering of retina in some vitreous gel, filling the eye. Each stage has its characteristics and particular properties, so doctors possibly could not take some of them into account, and thu …

Visit

github.com

Tasks

computer visionimage classificationtransfer learning

Languages

Ikizu

Similar

DhruvPremani1017/Diabetic-RetinopathyDiabetic Retinopathy DiagnosisZerXXX0/diabetic-retinopathy-severity-classificationIDRiD: Diabetic Retinopathy – Segmentation and Grading ChallengeUltra-Widefield Fundus Imaging for Diabetic RetinopathyM'Sila retinal fundus dataset for diabetic retinopathy

DhruvPremani1017/Diabetic-Retinopathy

This project uses a U-Net model to segment key diabetic retinopathy lesions from retinal images in t

Diabetic Retinopathy Diagnosis

Diabetic Retinopathy Diagnosis

Poster presented at the Deep Learning Indaba 2022 by Zephania Reuben

ZerXXX0/diabetic-retinopathy-severity-classification

Lightweight Diabetic Retinopathy Classifier using MobileViTV2. Model achieves 83% accuracy on the DD

IDRiD: Diabetic Retinopathy – Segmentation and Grading Challenge

International audience

Ultra-Widefield Fundus Imaging for Diabetic Retinopathy

Diabetic retinopathy (DR), a common and specific complication of diabetes mellitus, is one

M'Sila retinal fundus dataset for diabetic retinopathy

A private clinical dataset of 600 retinal fundus images collected at an ophthalmology clini