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Updated: Nov 21, 2025

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
Published on: November 23, 2019
Topological recovery for non-rigid 2D/3D registration of coronary artery models
Siyeop Yoon1, Chang Hwan Yoon2, Deukhee Lee1
15, Hwarang-ro 14-gil, Seongbuk-gu, Seoul,Center for Healthcare Robotics, Korea Institute of Science and Technology, South Korea; 5, Hwarang-ro 14-gil, Seongbuk-gu, Seoul, KIST School, Korea University of Science and Technology, South Korea.
Background And Objective:
Intra-operative X-ray angiography, the current standard method for visualizing and diagnosing cardiovascular disease, is limited in its ability to provide essential 3D information. These limitations are disadvantages in treating patients. For example, it is a cause of lowering the success rate of interventional procedures. Here, we propose a novel 2D-3D non-rigid registration method to understand vascular geometry during percutaneous coronary intervention.
Methods:
The proposed method uses the local bijection pair distance as a cost function to minimize the effect of inconsistencies from center-line extraction. Moreover, novel cage-based 3D deformation and multi-threaded particle swarm optimization are utilized to implement real-time registration. We evaluated the proposed method for 154 examinations from 10 anonymous patients by coverage percentage, comparing the average distance of the 2D extracted center-line with that of the registered 3D center-line.
Results:
The proposed 2D-3D non-rigid registration method achieved an average distance of 1.98 mm with a 0.54 s computation time. Additionally, in aiming to reduce the uncertainty of XA images, we used the proposed method to retrospectively visualize the connections between 2D vascular segments and the distal part of occlusions.
Conclusions:
Ultimately, the proposed 2D/3D non-rigid registration method can successfully register the 3D center-line of coronary arteries with corresponding 2D XA images, and is computationally sufficient for online usage. Therefore, this method can improve the success rate of such procedures as a percutaneous coronary intervention and provide the information necessary to diagnose cardiovascular diseases better.
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