Mi J, Zhou Y, Feng Q
School of Biomedical Engineering, Southern Medical University//Guangdong Provincial Key Laboratory of Medical Image Processing//Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou 510515, China.
Nan Fang Yi Ke Da Xue Xue Bao. 2023 Sep 20;43(9):1636-1643. doi: 10.12122/j.issn.1673-4254.2023.09.23.
To establish a 3D/2D registration method for preoperative CT and intra-operative X-ray images in imageguided spine surgery.
We propose a 3D/2D registration algorithm based on 3D image reconstruction. The algorithm performs 3D image reconstruction of 2D orthogonal view X-ray images, thus converting the problem into 3D/3D registration. By constructing an end-to-end framework that combines the two tasks of reconstruction and registration, the geodesic distance is measured in the 3D manifold space to complete the registration.
We conducted experiments on the public dataset CTSpine1k. The tests on two test sets with different initial registration errors showed that for data with small initial errors, the proposed algorithm achieved a rotation estimation error of 0.115±0.095° and a translation estimation error of 0.144±0.124 mm; for data with larger initial errors, a rotation estimation error of 0.792±0.659° and a translation estimation error of 0.867±0.701 mm were achieved.
The proposed method can achieve robust and accurate 3D/2D registration at a speed that meets real-time requirements to improve the performance of spine surgery navigation.
建立一种用于图像引导脊柱手术中术前CT与术中X射线图像的三维/二维配准方法。
我们提出一种基于三维图像重建的三维/二维配准算法。该算法对二维正交视图X射线图像进行三维图像重建,从而将问题转化为三维/三维配准。通过构建一个结合重建和配准两项任务的端到端框架,在三维流形空间中测量测地距离以完成配准。
我们在公共数据集CTSpine1k上进行了实验。在两个具有不同初始配准误差的测试集上的测试表明,对于初始误差较小的数据,所提算法实现了0.115±0.095°的旋转估计误差和0.144±0.124mm的平移估计误差;对于初始误差较大的数据,实现了0.792±0.659°的旋转估计误差和0.867±0.701mm的平移估计误差。
所提方法能够以满足实时要求的速度实现稳健且准确的三维/二维配准,以提高脊柱手术导航的性能。