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A multi-resolution multi-model method for coronary centerline extraction based on minimal path

Jia D, Shi W, Rueckert D, Liu L, Ourselin S, Zhuang X (2016)

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Publication Type: Conference contribution

Publication year: 2016

Journal

Publisher: Springer Verlag

Book Volume: 9805 LNCS

Pages Range: 320-328

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Bern, CHE

ISBN: 9783319437743

DOI: 10.1007/978-3-319-43775-0_29

Abstract

Extracting centerlines of coronary arteries is challenging but important in clinical applications of cardiac computed tomography angiography (CTA). Since manual annotation of coronary arteries is time-consuming, laborintensive and subject to intra- and inter-variations, we propose a new method to fully automatically extract the coronary centerlines. We first develop a new image filter which generates pixels with salient vessel features within a given window. This filter hence can capture sparsely distributed but important vessel points, enabling the minimal path (MP) process to track the key centerline points at different resolution of the images. Then, we reformulate the filter for multi-resolution fast marching, which not only can speed up the coronary tracking process, but also can help the front propagation to step over the indistinct segments of the coronary artery such as at the locations of stenosis. We embed this scheme into the MP framework to develop a multi-resolution multi-model approach (MMP), where the extracted centerlines from low-resolution MP serve as prior and constraints for the high-resolution process. We evaluated the performance of this method using the Rotterdam CTA training data and the coronary artery algorithm evaluation framework. The average inside of our extraction was 0.51 mm and the overlap was 72.9 %. The mean runtime on the original resolution CTA images was 3.4 min using the MMP method.

Involved external institutions

How to cite

APA:

Jia, D., Shi, W., Rueckert, D., Liu, L., Ourselin, S., & Zhuang, X. (2016). A multi-resolution multi-model method for coronary centerline extraction based on minimal path. In Hongen Liao, Guoyan Zheng, Su-Lin Lee, Philippe Cattin, Pierre Jannin (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 320-328). Bern, CHE: Springer Verlag.

MLA:

Jia, Dengqiang, et al. "A multi-resolution multi-model method for coronary centerline extraction based on minimal path." Proceedings of the 7th International Conference on Medical Imaging and Augmented Reality, MIAR 2016, Bern, CHE Ed. Hongen Liao, Guoyan Zheng, Su-Lin Lee, Philippe Cattin, Pierre Jannin, Springer Verlag, 2016. 320-328.

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