A Low-Cost Benchmarking Platform for Tracking Systems to Enable Augmented Surgery Tools in Clinical Practice
摘要
Augmented Reality (AR) is increasingly being adopted in surgical procedures. Identifying accurate and reliable tracking systems can enhance the effectiveness of AR assisted surgery. The study presents a benchmarking platform to evaluate the performance of different optical surgical tools tracking systems for AR applications, addressing the need for standardized comparison of tracking systems’ accuracy, repeatability, and reliability. A custom-built, cost-effective benchmarking platform was developed, and different quantitative evaluation metrics were employed to assess performances of Marker-Based (MB) tracking systems. Two types of measurements were performed: static, where metrics such as Target Registration Error (TRE) and tip stability as a measure of jitter were estimated, and dynamic, involving a measure of the deviation between the tracked tooltip trajectory and its GT. Three AR MB-tracking methods were tested: method 1, mono-RGB sensor tracking a planar image target; method 2, RGB-depth sensor tracking passive spherical markers; and method 3, mono-IR sensor tracking IR active markers. Significant performance differences were observed. Method 3 achieved the lowest TRE value of