A neural network approach to segment brain blood vessels in digital subtraction angiography.

ABSTRACT:

Background and objective

Cerebrovascular diseases (CVDs) affect a large number of patients and often have devastating outcomes. The hallmarks of CVDs are the abnormalities formed on brain blood vessels, including protrusions, narrows, widening, and bifurcation of the blood vessels. CVDs are often diagnosed by digital subtraction angiography (DSA) yet the interpretation of DSA is challenging as one must carefully examine each brain blood vessel. The objective of this work is to develop a computerized analysis approach for automated segmentation of brain blood vessels.

Methods

In this work, we present a U-net based deep learning approach, combined with pre-processing, to track and segment brain blood vessels in DSA images. We compared the results given by the deep learning app

SUBMITTER: Zhang M 

PROVIDER: S-EPMC7518214 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature