Segmentation of coronary arteries from CT angiography images

Abstract

We present an automated method for delineation of coronary arteries from Cardiac CT Angiography (CTA) images. Coronary arteries are narrow blood vessels and when imaged using CTA, appear as thin cylindrical structures of varying curvature. This appearance is often affected by heart motion and image reconstruction artifacts. Moreover, when an artery is diseased, it may appear as a non-continuous structure of widely varying width and image intensity. Defining the boundaries of the coronary arteries is an important and necessary step for further analysis and diagnosis of coronary disease. For this purpose, we developed a method using cylindrical structure modeling. For each vessel segment a best fitting cylindrical template is found. By applying this technique sequentially along the vessel, its entire volume can be reconstructed. The algorithm is seeded with a manually specified starting point at the most distal discernible portion of an artery and then it proceeds iteratively toward the aorta. The algorithm makes necessary corrections to account for CTA image artifacts and is able to perform in diseased arteries. It stops when it identifies the vessels junction with the aorta. Five cardiac 3D CT angiography studies were used for algorithm validation. For each study, the four longest visually discernible branches of the major coronary arteries were evaluated. Central axes obtained from our automated method were compared with ground truth markings made by an experienced radiologist. In 75% of the cases, our algorithm was able to extract the entire length of the artery from single initialization.