Towards Accurate and Complete Registration of Coronary Arteries in CTA Images
Coronary computed tomography angiography (CCTA) has been widely used nowadays. By combining multiple intra-subject CCTA images from different dates or different phases, cardiologists can monitor the disease progress, and researchers can explore the rules of coronary artery motion and changes within a cardiac cycle. For direct comparison and high efficiency, alignment of arteries is necessary. In this paper, we propose an automated method for accurate and complete registration of coronary arteries. Our method includes bifurcation matching, segment registration, and a novel approach to further improve the completeness of registration by combining the previous results and a level set algorithm. Our method is evaluated using 36 CCTA image pairs captured at different dates or different phases. The average distance error is \(0.044 \pm 0.008\) mm and the average correct rate of registration is 90.7%.
This work is supported by the National Natural Science Foundation of China under Grant 61622207.
- 3.Habert, S., Khurd, P., Chefd’Hotel, C.: Registration of multiple temporally related point sets using a novel variant of the coherent point drift algorithm: application to coronary tree matching. In: Medical Imaging 2013: Image Processing, vol. 8669, p. 86690M. International Society for Optics and Photonics (2013)Google Scholar
- 5.Leordeanu, M., Hebert, M.: A spectral technique for correspondence problems using pairwise constraints. In: Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV 2005) Volume 1, vol. 2, pp. 1482–1489, October 2005Google Scholar
- 6.Luo, Y., Feng, J., Xu, M., Zhou, J., Min, J.K., Xiong, G.: Registration of coronary arteries in computed tomography angiography images using hidden Markov model. In: Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1993–1996, August 2015Google Scholar
- 8.Scovanner, P., Ali, S., Shah, M.: A 3-dimensional SIFT descriptor and its application to action recognition. In: Proceedings of the 15th ACM International Conference on Multimedia, pp. 357–360. ACM (2007)Google Scholar