Abstract Machine learning (ML) algorithms have made a tremendous impact in the field of
medical imaging. While medical imaging datasets have been growing in size, a challenge …

Background Diabetic retinopathy (DR), whose standard diagnosis is performed by human
experts, has high prevalence and requires a more efficient screening method. Although …

Automatic screening of diabetic retinopathy (DR) is a well-identified area of research in the
domain of computer vision. It is challenging due to structural complexity and a marginal …

Diabetic Retinopathy (DR) is the most common cause of avoidable vision loss,
predominantly affecting the working-age population across the globe. Screening for DR …

Abstract Backround and Objectives Diabetic retinopathy is a microvascular complication of
diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the …

This paper presents an automated early diabetic retinopathy detection scheme from color
fundus images through improved segmentation strategies for optic disc and blood vessels …

Diabetic retinopathy (DR) is a complication of diabetes that exists throughout the world. DR
occurs due to a high ratio of glucose in the blood, which causes alterations in the retinal …

Retinal microaneurysms (MAs) are the earliest clinical sign of diabetic retinopathy disease.
Detection of MAs is crucial for the early diagnosis of diabetic retinopathy and prevention of …

The prediction and early diagnosis of eye diseases are critical for effective treatment and
prevention of vision loss. The identification of eye diseases has recently been the subject of …

This paper presents an improved diabetic retinopathy detection scheme by extracting
accurate area and ate number of microaneurysm from color fundus images. Regular …