Automated retinal image analysis holds prime significance in the accurate diagnosis of
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …

The blood vessels are the primary anatomical structure that can be visible in retinal images.
The segmentation of retinal blood vessels has been accepted worldwide for the diagnosis of …

Retinal vessel segmentation is an important task in medical image analysis and has a
variety of applications in the diagnosis and treatment of retinal diseases. In this paper, we …

Extraction or segmentation of organ vessels is an important task for surgical planning and
computer-aided diagnoses. This is a challenging task due to the extremely small size of the …

Automatic retinal blood vessel segmentation is a key link in the diagnosis of ophthalmic
diseases. Recent deep learning methods have achieved high accuracy in vessel …

Retinal vessel segmentation and centerline extraction are crucial steps in building a
computer-aided diagnosis system on retinal images. Previous works treat them as two …

Automatic retinal vessel segmentation is important for assisting clinicians in diagnosing
ophthalmic diseases. The existing deep learning methods remain constrained in instance …

Precise segmentation of retinal vessels is crucial for a computer-aided diagnosis system of
retinal fundus images. However, this task remains challenging due to large variations in …

Blood Vessels play a major role in our vision process. Likewise, the segmentation of theses
vascular structure of blood vessels segmentation projects as a critical part in diagnosis of the …

Diabetic retinopathy is a common disease among people with diabetes. Early stage
diagnosis and treatment of diabetic retinopathy are essential to prevent the progression of …