Metrological Analysis of HoloLens 2 for Visual Marker-Based Surgical Navigation

Although the research on medical navigation systems dates back to the second half of the 20th century, the emergence of modern technologies offers new prospects for their application. One of the technologies that has been investigated in recent years for its potential in clinician support systems is augmented reality. Many AR solutions utilize head-mounted displays, allowing for the integration during medical procedures. These displays are equipped with cameras that can provide data for marker-based navigation. However, before implementing such approaches in real-world applications, it is crucial to assess the precision of marker detection. Therefore, in this paper we present a metrological analysis of the detection of two most common marker types, namely QR codes and ArUco markers, using Hololens 2 and dedicated algorithms designed for this specific purpose. Our study consisted of two different measuring setups: one to investigate the effect of different distances and the other to investigate the effect of angles on position error. The results showed that QR codes can be detected from a maximum distance of 750mm (for a 75mm size marker), while ArUco markers can be detected from distances as far as 1250mm, even for a marker as small as 2.3 cm. However, the standard deviation of the average measurement of ArUco marker size is greater than that of QR codes. The results obtained suggest that it is possible to detect ArUco markers in sizes and distances suitable for medical settings using HoloLens 2 and dedicated software. Therefore, the results of this study could potentially pave the way for the development of a marker-based method for medical navigation in the future.