冠状动脉疾病
投影(关系代数)
迭代重建
冠状动脉
人工智能
三维重建
计算机视觉
计算机科学
点云
动脉
放射科
医学
算法
心脏病学
作者
Yaosong Jia,Deqiang Xiao,Qing Yan,Mingwei Gao
标识
DOI:10.1145/3524086.3524097
摘要
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.
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