Coronary Wall Segmentation in CCTA Scans Via a Hybrid Net with Contours Regularization

Providing closed and well-connected boundaries of coronary artery is essential to assist cardiologists in the diagnosis of coronary artery disease (CAD). Recently, several deep learning-based methods have been proposed for boundary detection and segmentation in a medical image. However, when applied to coronary wall detection, they tend to produce disconnected and inaccurate boundaries. In this paper, we propose a novel boundary detection method for coronary arteries that focuses on the continuity and connectivity of the boundaries. In order to model the spatial continuity of consecutive images, our hybrid architecture takes a volume (i.e., a segment of the coronary artery) as input and detects the boundary of the target slice (i.e., the central slice of the segment). Then, to ensure closed boundaries, we propose a contour-constrained weighted Hausdorff distance loss. We evaluate our method on a dataset of 34 patients of coronary CT angiography scans with curved planar reconstruction (CCTA-CPR) of the arteries (i.e., cross-sections). Experiment results show that our method can produce smooth closed boundaries outperforming the state-of-the-art accuracy.

1. Introduction

Coronary artery disease (CAD), the narrowing or blockage of the coronary arteries, is one of the leading causes of death around the world. It is usually caused by atherosclerosis (i.e., the build up of plaques on the inner walls of arteries) and can restrict blood flow to the heart muscle by physically clogging the artery. This is the cause of abnormal artery functions and other related diseases such as angina, heart attack, and ischemia. The CAD diagnosis is a complicated and time-consuming procedure requiring expertise of well-trained cardiologists. In particular, precise blood vessel wall segmentation of the coronary artery plays a fundamental role in the whole procedure. With the advances of automatic vessel extraction techniques, centerlines of the main coronary arteries can be extracted given a volume of CCTA scans of the heart. Then a curved planar reconstruction (CPR) is operated to extract cross-section slices along the curved centerline and rearrange them into a new volume (i.e., CPR artery), from which cardiologists will segment the coronary wall.