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

This paper presents a comprehensive review of retinal blood vessel segmentation based on
deep learning. The geometric characteristics of retinal vessels reflect the health status of …

Vessel segmentation is critical for disease diagnosis and surgical planning. Recently, the
vessel segmentation method based on deep learning has achieved outstanding …

ABSTRACT A real-time architecture of medical image semantic segmentation called Fully
Convolution dense Dilated Network, is proposed to improve the segmentation efficiency …

Segmentation of blood vessels becomes an initial critical step in medical imaging because it
is a key item for the diagnosis of many diseases in different fields including ophthalmology …

Until now, the human expert segments retinal blood vessels manually in fundus images to
inspect human retinal-related diseases, such as diabetic retinopathy and vascular occlusion …

Retinal fundus vessels contain rich geometric features, including both thick and thin vessels,
which is particularly important for accurate clinical diagnosis of cardiovascular diseases …

The first diagnosis of diabetic retinopathy (DR) must include lesion segmentation. As it takes
a lot of time and effort to label lesions, automatic segmentation methods have to be created …

Glaucoma is an irreversible neurodegenerative disease, where intraocular hypertension is
developed due to the increased aqueous humor and blockage of the drainage system …

Aim: With advances in computer science techniques, such as artificial intelligence (AI) and
deep learning (DL), opportunities for the detection of DR at the early stages have increased …