<p>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 <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(3.578 \pm 2.836 \text { mm}.\)</EquationSource> </InlineEquation> Method 1 exhibited the best tip stability with a jitter value of <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(1.435 \pm 0.824 \text { mm}.\)</EquationSource> </InlineEquation> Method 2 obtained the minimum trajectory distance in dynamic tests. The benchmarking platform demonstrated its effectiveness in evaluating and comparing different AR tracking methods. This study enables the optimization of tracking system selection for use in the operating room, and facilitating the integration of AR as a supportive technology in surgical practice.</p>

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A Low-Cost Benchmarking Platform for Tracking Systems to Enable Augmented Surgery Tools in Clinical Practice

  • Federico Salerno,
  • Alessandro Contenti,
  • Luca Ulrich,
  • Sandro Moos,
  • Attilio Fiandrotti,
  • Enrico Vezzetti

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 \(3.578 \pm 2.836 \text { mm}.\) Method 1 exhibited the best tip stability with a jitter value of \(1.435 \pm 0.824 \text { mm}.\) Method 2 obtained the minimum trajectory distance in dynamic tests. The benchmarking platform demonstrated its effectiveness in evaluating and comparing different AR tracking methods. This study enables the optimization of tracking system selection for use in the operating room, and facilitating the integration of AR as a supportive technology in surgical practice.