Diabetic Retinopathy (DR) is a leading cause of vision loss worldwide. Early detection and timely intervention are crucial for preventing vision impairment. This research aims to develop an AI-powered system for the early detection of Diabetic Retinopathy using fundus images. The proposed system utilizes advanced machine learning techniques to analyze fundus images and identify early signs of Diabetic Retinopathy. By leveraging annotated datasets, the model is trained to accurately classify images as healthy or indicative of Diabetic Retinopathy. The developed system offers a potential solution to the challenges associated with traditional DR screening methods, such as the timeconsuming nature of manual examination and the need for specialized equipment. By enabling early detection, this technology can significantly improve patient outcomes and reduce the burden of vision loss due to Diabetic Retinopathy.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Detection and Classification of Retinal Fundus in Diabetic Retinopathy using Modern Artificial Intelligence and Machine Learning Approaches


    Contributors:


    Publication date :

    2024-11-06


    Size :

    479697 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Segmentation of Diabetic Retinopathy Based on Retinal Fundus Images Using Thresholding Technique

    Ali, Nur Hasanah / Hamzah, Nur Asyiqin Amir / Saad, Norhashimah Mohd et al. | Springer Verlag | 2022

    Free access

    An Ensemble Deep Learning Approach for Diabetic Retinopathy Detection using Fundus Image

    Johnson, Sandra / J R, Lourdu Jennifer / Karthikeyan, G. et al. | IEEE | 2022



    Detection and Classification of Diabetic Retinopathy using Raspberry PI

    Vidhya Lavanya, R / EP, Sumesh / Jayakumari, C et al. | IEEE | 2020


    Integration of Artificial Intelligence for a low-cost diagnosis of Diabetic Retinopathy

    Ahmed, Mohammed Shafeeq / Mithun, Tiruvedula / Nagaraju, Regonda et al. | IEEE | 2021