Automatic diagnosis of coronary artery stenosis by deep learning based on X-ray coronary angiography.

ABSTRACT:

Background

Coronary artery disease (CAD) is a leading cause of global mortality, primarily due to the accumulation of atheromatous plaques in coronary arteries. The current diagnostic standards include X-ray coronary angiography, which evaluates morphological features of the coronary arteries. The primary goal of this modality is to quantify stenosis severity, but variability and complexities in the resultant images make consistent interpretation challenging. This study developed a deep learning-based approach for segmenting and grading vessel stenosis via X-ray coronary angiography.

Methods

Based on 383 angiographic images from 168 patients, we developed a dual-output deep convolutional neural network (CNN) to automatically diagnose stenosis. For clinical relevance, we manu

SUBMITTER: Mao C 

PROVIDER: S-EPMC12591895 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature