U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …

Retinal vessel segmentation algorithms are a fundamental component of automatic retinal
disease screening systems. This work examines the blood vessel segmentation …

Fundus imaging is a retinal image modality for capturing anatomical structures and
abnormalities in the human eye. Fundus images are the primary tool for observation and …

Retinal image analysis holds an imperative position for the identification and classification of
retinal diseases such as Diabetic Retinopathy (DR), Age Related Macular Degeneration …

Glaucoma is the second leading cause of loss of vision in the world. Examining the head of
optic nerve (cup‐to‐disc ratio) is very important for diagnosing glaucoma and for patient …

Objective: Diabetic retinopathy (DR) is characterized by the progressive deterioration of
retina with the appearance of different types of lesions that include micro-aneurysms …

The classification of retinal vessels into artery/vein (A/V) is an important phase for
automating the detection of vascular changes, and for the calculation of characteristic signs …

Retinal illnesses such as diabetic retinopathy (DR) are the main causes of vision loss. In the
early recognition of eye diseases, the segmentation of blood vessels in retina images plays …

Background and objective Retinal blood vessel segmentation is a prominent task for the
diagnosis of various retinal pathology such as hypertension, diabetes, glaucoma, etc. In this …

Early detection of retinal diseases is one of the most important means of preventing partial or
permanent blindness in patients. In this research, a novel multi-label classification system is …