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

  • Liu Liu
  • Jin Xu
  • Zheng Liu
Article
  • 33 Downloads

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.

Keywords

Coronary centerline Coronary lumen Lumen segmentation 

Notes

Acknowledgements

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

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Nanjing University of Posts and TelecommunicationsNanjingChina
  2. 2.The Third Affiliated Hospital of Nanjing University of Chinese MedicineNanjingChina

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