Coronary artery vessel tree enhancement in three-dimensional computed tomography angiography

Abstract

Coronary artery segmentation in 3D images is a fundamental step in evaluating the degree of Coronary Artery Disease (CAD) in cardiac clinical diagnosis and surgical planning. In this paper, we study the effect of vessel filtering and enhancement on coronary artery segmentation from Computed Tomography Angiography (CTA) datasets. The method mainly consists of two steps: (1) CTA datasets enhancement using Hessian-based analysis; and (2) coronary vessels segmentation in enhanced images using Otsu thresholding. The experiments are carried on 18 different CTA datasets and segmentation results of enhanced and non-enhanced datasets are quantitatively measured and compared using three different evaluation metrics. Experimental results show that segmenting coronary vessels in enhanced CTA images gives more accurate extraction of coronary arteries than non-enhanced images.