Designing deep learning based methods with medical images has always been an attractive
area of research to assist clinicians in rapid examination and accurate diagnosis. Those …

Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …

As the only blood vessels that can directly be seen in the whole body, pathological changes
in retinal vessels are related to the metabolic state of the whole body and many systems …

Artificial intelligence (AI) has emerged as a transformative tool in the field of ophthalmology,
revolutionizing disease diagnosis and management. This paper provides a comprehensive …

If Diabetic Retinopathy (DR) patients do not receive quick diagnosis and treatment, they may
lose vision. DR, an eye disorder caused by high blood glucose, is becoming more prevalent …

Background Diabetic retinopathy (DR) produces bleeding, exudation, and new blood vessel
formation conditions. DR can damage the retinal blood vessels and cause vision loss or …

Diabetic Retinopathy (DR) is a retinal condition that leads to gradual degeneration of the
retina and eventual blindness, so early detection and evaluation of disease development …

Recently, academic and clinical communities have paid increasing attention to design
computer-aided diagnosis methods for automatic and accurate diabetic retinopathy (DR) …

The disease with the fastest global growth rate, diabetes, has numerous complications.
Diabetic retinopathy (DR), which results in retinal lesions that affect vision, is one of these …

This paper presents a novel approach that merges a lightweight parallel depth-wise
separable convolutional neural network (LPDCNN) with a ridge regression extreme learning …