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Extraction of coronary arteries centerlines from CT angiography images Recent developments in CT angiography (CTA) imaging allow for the acquisition of three-dimensional volumetric images of the entire heart region. These images are vital in obtaining precise information about the structure of the coronary artery tree and additionally, help to make accurate clinical diagnosis. In this work we focus on automated reconstruction of coronary artery centerlines from CTA images. Defining the structure of the coronary artery is the important step toward the automated diagnosis of the heart disease. 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. To find the geometrical structure of a coronary artery, we developed a method using tubular model matching. By finding best fitting cylindrical template sequentially along the vessel, its entire volume can be reconstructed. The algorithm is seeded with a manually specified starting points at the distal 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. For algorithm validation we use numerous cardiac 3D CT angiography studies. |