TY - GEN
T1 - A Method for Reconstructing 3D Skeleton of Coronary Artery from 2D X-ray Angiographic Images
AU - Jia, Yaosong
AU - Xiao, Deqiang
AU - Yan, Qing
AU - Gao, Mingwei
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/3/18
Y1 - 2022/3/18
N2 - X-ray angiographic imaging is commonly used for diagnosis and treatment planning of coronary artery disease. However, it is produced via perspective projection principle, causing two-dimensional (2D) views with vessel segments overlapping and shortening, which prevents physicians from observing the vascular structure clearly. Reconstructing a three-dimensional (3D) skeleton of coronary artery from 2D X-ray angiographic images is able to improve the accuracy and efficiency for diagnosis of coronary heart disease. Therefore, we propose a novel method to reconstruct the accurate 3D coronary artery skeletons from 2D X-ray angiographic images. Specifically, the 3D coronary artery skeleton is represented with a point-cloud, the impact of rigid motions including device and patient movement are both considered in our method. Additionally, an iterative correction method is introduced to refine the coarse reconstruction results. Evaluation with 10 cases of clinical data show that average reprojection error of our reconstructed models is 0.114 ± 0.051 mm, which is significantly reduced compared with that of related methods, and meets clinical requirements.
AB - X-ray angiographic imaging is commonly used for diagnosis and treatment planning of coronary artery disease. However, it is produced via perspective projection principle, causing two-dimensional (2D) views with vessel segments overlapping and shortening, which prevents physicians from observing the vascular structure clearly. Reconstructing a three-dimensional (3D) skeleton of coronary artery from 2D X-ray angiographic images is able to improve the accuracy and efficiency for diagnosis of coronary heart disease. Therefore, we propose a novel method to reconstruct the accurate 3D coronary artery skeletons from 2D X-ray angiographic images. Specifically, the 3D coronary artery skeleton is represented with a point-cloud, the impact of rigid motions including device and patient movement are both considered in our method. Additionally, an iterative correction method is introduced to refine the coarse reconstruction results. Evaluation with 10 cases of clinical data show that average reprojection error of our reconstructed models is 0.114 ± 0.051 mm, which is significantly reduced compared with that of related methods, and meets clinical requirements.
KW - 3D reconstruction
KW - Coronary artery skeleton
KW - Cubic B-spline
KW - Point cloud
KW - X-ray angiographic image
UR - http://www.scopus.com/inward/record.url?scp=85128595681&partnerID=8YFLogxK
U2 - 10.1145/3524086.3524097
DO - 10.1145/3524086.3524097
M3 - Conference contribution
AN - SCOPUS:85128595681
T3 - ACM International Conference Proceeding Series
SP - 70
EP - 75
BT - IMIP 2022 - Proceedings of 2022 4th International Conference on Intelligent Medicine and Image Processing
PB - Association for Computing Machinery
T2 - 4th International Conference on Intelligent Medicine and Image Processing, IMIP 2022
Y2 - 18 March 2022 through 21 March 2022
ER -