Multislice CT angiography (MSCTA) is an emerging modality for assessing the coronary arteries. The use of MSCTA for coronary artery disease (CAD) quantification requires an assessment procedure of the coronary arteries that is automated as much as possible. We present an algorithm for the segmentation of the coronary tree with simultaneous extraction of the centerline and the tree-structure. Our approach limits the required user interaction to the placement of one landmark in the left and right main coronary artery respectively. The whole segmentation process takes about 15 s on a mid-sized PC (1GHz) including a real-time visualization of the segmentation in progress.The presented method combines a fast region expansion method (fast marching / front propagation) with heuristic reasoning. The spreading front is monitored for front-splitting enabling branch detection and simultaneous tree reconstruction of the segmented object. This approach allows for the individual treatment of tree-branches with respect to, e.g., threshold settings and reasoning on tree and sub-tree level. This approach can be applied quite generally to the segmentation of tree-like structures.The segmentation results support efficient reporting by enabling automatic generation of overview visualizations, guidance for virtual endoscopy, generation of curved MPRs along the vessels, or cross-sectional area graphs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.