Jeong Heeryeol, Park Taeyong, Khang Seungwoo, Koo Kyoyeong, Shin Juneseuk, Kim Kyung Won, Lee Jeongjin
School of Computer Science and Engineering , Soongsil University , 369 Sangdo-Ro, Dongjak-Gu, Seoul, 06978 Korea.
Department of Biomedical Informatics , Hallym University Medical Center , 22, Gwanpyeong-ro, 170 beon- gil, Dongan-gu, Anyang-si, Gyeonggi-do 14068 Korea.
Biomed Eng Lett. 2022 Dec 12;13(1):65-72. doi: 10.1007/s13534-022-00254-8. eCollection 2023 Feb.
In this paper, we propose an accurate and rapid non-rigid registration method between blood vessels in temporal 3D cardiac computed tomography angiography images of the same patient. This method provides auxiliary information that can be utilized in the diagnosis and treatment of coronary artery diseases. The proposed method consists of the following four steps. First, global registration is conducted through rigid registration between the 3D vessel centerlines obtained from temporal 3D cardiac CT angiography images. Second, point matching between the 3D vessel centerlines in the rigid registration results is performed, and the corresponding points are defined. Third, the outliers in the matched corresponding points are removed by using various information such as thickness and gradient of the vessels. Finally, non-rigid registration is conducted for hierarchical local transformation using an energy function. The experiment results show that the average registration error of the proposed method is 0.987 mm, and the average execution time is 2.137 s, indicating that the registration is accurate and rapid. The proposed method that enables rapid and accurate registration by using the information on blood vessel characteristics in temporal CTA images of the same patient.
在本文中,我们提出了一种针对同一患者的颞部三维心脏计算机断层扫描血管造影图像中血管之间的精确且快速的非刚性配准方法。该方法提供了可用于冠状动脉疾病诊断和治疗的辅助信息。所提出的方法包括以下四个步骤。首先,通过对从颞部三维心脏CT血管造影图像中获取的三维血管中心线进行刚性配准来进行全局配准。其次,对刚性配准结果中的三维血管中心线进行点匹配,并定义相应的点。第三,利用血管厚度和梯度等各种信息去除匹配对应点中的异常值。最后,使用能量函数进行分层局部变换的非刚性配准。实验结果表明,所提出方法的平均配准误差为0.987毫米,平均执行时间为2.137秒,表明配准准确且快速。所提出的方法通过利用同一患者颞部CTA图像中的血管特征信息实现了快速且准确的配准。