A Patient-Specific 3Dt Coronary Artery Motion Modeling Method Using Hierarchical Deformation with Electrocardiogram+

Sensors

Changhwan Yoon¹  Deukhee Lee²  Siyeop Yoon²  EunJu Chun³ 

[1] Cardiovascular Center, Seoul National University Bundang Hospital, Seongnam 13620, Korea;Center for Medical Robotics, Korea Institute of Science and Technology, 5, Hwarang-ro 14-gil, Seongbuk-gu, Seoul 02792, Korea;Department of Radiology, Seoul National University Bundang Hospital, Seongnam 13620, Korea;

关键词: 3D+t modeling;    coronary artery;    non-rigid registration;    cage deformation;    4D CT;   

DOI  :  10.3390/s20195680

来源: DOAJ

【 摘 要 】

Cardiovascular-related diseases are one of the leading causes of death worldwide. An understanding of heart movement based on images plays a vital role in assisting postoperative procedures and processes. In particular, if shape information can be provided in real-time using electrocardiogram (ECG) signal information, the corresponding heart movement information can be used for cardiovascular analysis and imaging guides during surgery. In this paper, we propose a 3D+t cardiac coronary artery model which is rendered in real-time, according to the ECG signal, where hierarchical cage-based deformation modeling is used to generate the mesh deformation used during the procedure. We match the blood vessel’s lumen obtained from the ECG-gated 3D+t CT angiography taken at multiple cardiac phases, in order to derive the optimal deformation. Splines for 3D deformation control points are used to continuously represent the obtained deformation in the multi-view, according to the ECG signal. To verify the proposed method, we compare the manually segmented lumen and the results of the proposed method for eight patients. The average distance and dice coefficient between the two models were 0.543 mm and 0.735, respectively. The required time for registration of the 3D coronary artery model was 23.53 s/model. The rendering speed to derive the model, after generating the 3D+t model, was faster than 120 FPS.

【 授权许可】

Unknown