Multi-resolution 2D-3D registration of vascular intervention based on normalized mutual information and gradient difference fusion

Jun Wang; Zhigang Ning; Xiangyun Liao; Qiong Wang

doi:10.1117/12.2636936

29 April 2022 Multi-resolution 2D-3D registration of vascular intervention based on normalized mutual information and gradient difference fusion

Jun Wang, Zhigang Ning, Xiangyun Liao, Qiong Wang

Author Affiliations +

Proceedings Volume 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022); 1224716 (2022) https://doi.org/10.1117/12.2636936
Event: 2022 International Conference on Image, Signal Processing, and Pattern Recognition, 2022, Guilin, China

Abstract

The registration between intraoperative 2D digital subtraction angiography and preoperative 3D computed tomography angiography can improve the visual perception of doctors during vascular interventional surgery and provide threedimensional information of blood vessels. Therefore, improving the accuracy and robustness of 2D-3D vascular registration is the key to vascular interventional surgery. In this paper, we propose a similarity measure that fuses normalized mutual information with gradient difference and adds a multi-resolution strategy to the registration framework. Experiments show that the mTRE of the proposed method is 2.1mm, and the time of each registration iteration is 174.6s. Compared with normalized mutual information and gradient difference, the proposed method has higher accuracy and faster efficiency, and achieves better results in a shorter time.

Citation Download Citation

Jun Wang, Zhigang Ning, Xiangyun Liao, and Qiong Wang "Multi-resolution 2D-3D registration of vascular intervention based on normalized mutual information and gradient difference fusion", Proc. SPIE 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022), 1224716 (29 April 2022); https://doi.org/10.1117/12.2636936

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