A Novel Registration Method for a Mixed Reality Navigation System Based on a Laser Crosshair Simulator: A Technical Note

Abstract

Mixed Reality Navigation (MRN) is pivotal in augmented reality-assisted intelligent neurosurgical interventions. However, existing MRN registration methods face challenges in concurrently achieving low user dependency, high accuracy, and clinical applicability. This study proposes and evaluates a novel registration method based on a laser crosshair simulator, evaluating its feasibility and accuracy. A novel registration method employing a laser crosshair simulator was introduced, designed to replicate the scanner frame’s position on the patient. The system autonomously calculates the transformation, mapping coordinates from the tracking space to the reference image space. A mathematical model and workflow for registration were designed, and a Universal Windows Platform (UWP) application was developed on HoloLens-2. Finally, a head phantom was used to measure the system’s target registration error (TRE). The proposed method was successfully implemented, obviating the need for user interactions with virtual objects during the registration process. Regarding accuracy, the average deviation was 3.7 ± 1.7 mm. This method shows encouraging results in efficiency and intuitiveness and marks a valuable advancement in low-cost, easy-to-use MRN systems. The potential for enhancing accuracy and adaptability in intervention procedures positions this approach as promising for improving surgical outcomes.

The Feasibility and Accuracy of Holographic Navigation with Laser Crosshair Simulator Registration on a Mixed-Reality Display

“…The LCS, as depicted in Figure 3, was designed to address the challenges of scanner tracking in MRN. Conventional automatic registration systems often rely on a reference array attached to the scanner, aligning images with a universal coordinate framework such as the world coordinate system [7]. However, the LCS introduces a novel approach by employing dual laser emitters and a specialized MR interface to overcome disruptions in optical tracking caused by user movement or scanner activities in HMDs (see Figure 3B).…”

“…Additionally, fiducial markers were segmented, and their centroids were marked to elaborate a series of accuracy metrics quantitatively (as indicated in Section 2.4.2). Furthermore, for each case, critical anatomical structures (such as ventricles, arteries, venous sinuses, pyramidal tracts, optic radiations, frontal sinuses, and scalp quadrants) upon availability of according data sets, as well as models for surgical guidance (such as puncture paths for reaching hemorrhage, endoscopic pathways, and the bone flaps suitable for port surgery with introducer assistance), were individually segmented [7,8,23,27], allowing to simulate the visualization environment in clinical settings closely and to evaluate the MRN system's computational load capacity for rendering multiple models. It should be noted, however, that due to individual variations and different surgical plans, these structures were not used for accuracy assessment.…”

“…While automatic methods are lauded for their low user dependency input and reduced registration error, they also show some drawbacks. These especially include their substantial hardware requirements and the necessity of specialized operation rooms, factors that significantly elevate the cost and limit their widespread adoption [7,8]. In response to these challenges, there has been a shift towards exploring cost-effective alternatives, particularly in augmented reality (AR) and mixed reality (MR) technologies [9][10][11][12][13][14][15][16][17][18][19][20].…”

“…These technologies, particularly when implemented through a head-mounted display (HMD), offer an innovative approach for navigation. They provide an immersive, interactive experience, allowing for intuitive preoperative planning and surgical guidance, a concept called mixed reality navigation (MRN) [7,8,11,12,[21][22][23]. Unlike conventional systems, MRN incorporates user-friendly interfaces and leverages emerging technologies to enhance accuracy and adaptability in surgical procedures [12,21,22,[24][25][26].…”

“…The development of the laser crosshair simulator (LCS) within the MRN framework marks a significant advancement [7]. The LCS-MRN system, mirroring the automatic registration paradigm of conventional systems, aims to (1) reproduce the relationship between the reference scan and the physical patient, (2) establish an initial virtual-to-physical space registration, and (3) maintain this alignment through continuous tracking (see Figure 1C).…”