ARCHIVES
Research Article
Design and Implementation of Retinal Eye Disease Detection Based on Machine Learning
Dr. Sanjay Asutkar1
Khushal Masarkar2
Meenakshi Atalkar3
12Professor, Electronics and communication Engineering, Tulsiramji Gaikwad-Patil College of Engineering & Technology, Nagpur, Maharashtra, India. 3PG Scholar, Electronics and communication Engineering, Tulsiramji Gaikwad-Patil College of Engineering & Technology, Nagpur, Maharashtra, India.
Published Online: March-April 2024
Pages: 91-93
Cite this article
No DOIAbstract
Abstract: Disease, retinal vein occlusion (blockage of a retinal vein), or diabetes mellitus, which induces fragility in blood vessels, making them prone to damage. The presence of hemorrhages in the retina serves as a primary indicator of diabetic retinopathy. The severity of the disease can be assessed based on the number and morphology of these hemorrhages. This study aims to achieve several objectives, including the detection of blood vessels, identification of hemorrhages, and classification of diabetic retinopathy into traditional, moderate, and non-proliferative stages (NPDR).
Related Articles
2024
Embedding Artificial Intelligence for Personal Voice Assistant Using NLP
2024
Analysis of Pedestrian Steel Bridge subjected the Seismic Load and Wind Load using Damper at different Span
2024
Review Paper on Comparison of Asymmetric and Symmetric RCC Building with Soil Structure Interaction by Dynamic Loading
2024
BLYNK RFID and Retinal Lock Access System
2024
ML-Driven Facial Synthesis from Spoken Words Using Conditional GANs
2024
