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Automatic segmentation of coronary lumen based on minimum path and image fusion from cardiac computed tomography images

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Abstract

Segmentation of the coronary lumen is a challenging aspect in the clinical application of cardiac computed tomography. In this paper, a new method is proposed for automatic segmentation of the coronary lumen. The proposed method is based on the directional minimum path and level-set segmentation on a cross-sectional fusion image. The directional minimum path is first used to automatically track the centerlines of the main coronary branches along a region of interest, providing the location of the center of the coronary lumen. Then, based on this centerline, cross-sectional images of the cardiac computed tomography volume are calculated to reconstruct a three-dimensional stacked image. To increase the success rate of lumen segmentation, the three-dimensional stacked image was enhanced using the proposed fusion method. The proposed fusion method included a gray filter that decreases noise, and a measure of the Vesselness that can enhance the coronary structure. Adaptive weighted fusion is then proposed to fuse the enhanced images. Finally, a level-set algorithm was used to segment the coronary lumen in the cross-sectional fused images. The proposed method was validated for the three main coronary branches. The Dice coefficients were 83.8% for the right coronary artery, 82.5% for the left anterior descending artery, and 83.9% for the left circumflex artery, respectively.

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Acknowledgements

This work was jointly supported by Natural Science Foundation of Jiangsu Province (BK20140896), and NPTSF (NY213110, NY214121).

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Authors and Affiliations

  1. Nanjing University of Posts and Telecommunications, Nanjing, China

    Liu Liu & Jin Xu

  2. The Third Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China

    Zheng Liu

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  1. Liu Liu
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  2. Jin Xu
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  3. Zheng Liu
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Correspondence to Liu Liu.

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Liu, L., Xu, J. & Liu, Z. Automatic segmentation of coronary lumen based on minimum path and image fusion from cardiac computed tomography images. Cluster Comput 22 (Suppl 1), 1559–1568 (2019). https://doi.org/10.1007/s10586-018-2548-6

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  • DOI: https://doi.org/10.1007/s10586-018-2548-6

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