Robust model-based centerline extraction of vessels in CTA data

Thomas Beck; Christina Biermann; Dominik Fritz; Rüdiger Dillmann

doi:10.1117/12.810753

27 March 2009 Robust model-based centerline extraction of vessels in CTA data

Thomas Beck, Christina Biermann, Dominik Fritz, Rüdiger Dillmann

Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 72593O (2009) https://doi.org/10.1117/12.810753
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Extracting the centerline of blood vessels is a frequently used technique to assist the physician in the diagnosis of common artery disease in CTA images. Thereby, a robust and precise computation of the centerline is an essential prerequisite. In this paper we present a novel approach to robustly model the vessel tree and to compute its centerline. The algorithm is initialized with two clicks from the physician, which mark the start and end point of the vessel to be examined. Our approach is divided into two consecutive steps. In the first step, a section of the vessel tree is mapped to the model so that the desired centerline is entirely included. After the generation of the model, the centerline can easily be extracted in the second step. The robust and efficient extraction of required model parameters is performed by a ray-casting approach. The proposed method determines a set of points on the vascular wall. The analysis of these points using the principal component analysis provides all parameters needed for modeling the vessel. The proposed technique reduces computation time and does not require a segmentation of the vessel lumen to determine the centerline of the vessel. Furthermore, a priori knowledge of vessel structures is incorporated to improve robustness in the presence of pathological deformations.

Citation Download Citation

Thomas Beck, Christina Biermann, Dominik Fritz, and Rüdiger Dillmann "Robust model-based centerline extraction of vessels in CTA data", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72593O (27 March 2009); https://doi.org/10.1117/12.810753

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