Automated blood vessel segmentation plays an important role in the diagnosis and treatment of various cardiovascular and ophthalmologic diseases. In this paper, a novel unsupervised segmentation algorithm is proposed to extract blood vessels from fundus images. At first, an enhanced vessel image is generated by morphological reconstruction, and then divided into three parts: preliminary vessel ...

The segmentation of retinal vessels plays an essential role in the early recognition ophthalmic diseases clinics. Increasingly, approaches based on deep learning have been pushing vessel performance, yet it is still a challenging problem due to complex structure and lack precisely labeled samples. In this paper, we propose self-paced dual-axis attention fusion network (SPDAA-Net). Firstly, mech...

Optical Coherence Tomography Angiography (OCTA) is a non-invasive imaging technique that has been increasingly used to image the retinal vasculature at capillary level resolution. However, automated segmentation of vessels in OCTA under-studied due various challenges such as low visibility and high vessel complexity, despite its significance understanding many vision-related diseases. In additi...