Deep learning segmentation of major vessels in X-ray coronary angiography.

ABSTRACT: X-ray coronary angiography is a primary imaging technique for diagnosing coronary diseases. Although quantitative coronary angiography (QCA) provides morphological information of coronary arteries with objective quantitative measures, considerable training is required to identify the target vessels and understand the tree structure of coronary arteries. Despite the use of computer-aided tools, such as the edge-detection method, manual correction is necessary for accurate segmentation of coronary vessels. In the present study, we proposed a robust method for major vessel segmentation using deep learning models with fully convolutional networks. When angiographic images of 3302 diseased major vessels from 2042 patients were tested, deep learning networks accurately identified and segmented t

SUBMITTER: Yang S 

PROVIDER: S-EPMC6858336 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature