Hsiao Yu-Ching, Fang Jing-Jing
Department of Mechanical Engineering, National Cheng Kung University, Tainan 701, Taiwan.
Bioengineering (Basel). 2023 Mar 6;10(3):335. doi: 10.3390/bioengineering10030335.
Computer-aided surgical planning has been widely used to increase the safety and predictability of surgery. The validation of the target of surgical planning to surgical outcomes on a patient-specific model is an important issue. The aim of this research was to develop a robust superposition method to assess the deviation of planning and outcome by using the symmetrical characteristic of the affected target. The optimal symmetry plane (OSP) of an object is usually used to evaluate the degree of symmetry of an object. We proposed a refined OSP-based contouring method to transfer a complex three-dimensional superposition operation into two dimensions. We compared the typical iterative closest point (ICP) algorithm with the refined OSP-based contouring method and examined the differences between them. The results using the OSP-based method were much better than the traditional method. As for processing time, the OSP-based contouring method was 11 times faster than the ICP method overall. The proposed method was not affected by the metallic artifacts from medical imaging or geometric changes due to surgical intervention. This technique can be applied for post-operative assessment, such as quantifying the differences between surgical targets and outcomes as well as performing long-term medical follow-up.
计算机辅助手术规划已被广泛应用于提高手术的安全性和可预测性。在患者特异性模型上验证手术规划目标与手术结果是一个重要问题。本研究的目的是开发一种稳健的叠加方法，利用受影响目标的对称特性来评估规划与结果的偏差。物体的最佳对称平面（OSP）通常用于评估物体的对称程度。我们提出了一种基于OSP的改进轮廓提取方法，将复杂的三维叠加操作转换为二维操作。我们将典型的迭代最近点（ICP）算法与基于OSP的改进轮廓提取方法进行了比较，并研究了它们之间的差异。使用基于OSP方法的结果比传统方法要好得多。在处理时间方面，基于OSP的轮廓提取方法总体上比ICP方法快11倍。所提出的方法不受医学成像中的金属伪影或手术干预引起的几何变化的影响。该技术可应用于术后评估，如量化手术目标与结果之间的差异以及进行长期医学随访。
