Robot-assisted minimally invasive surgery has shown to improve patient outcomes, as well as reduce complications and recovery time for several clinical applications. However, increasingly configurable robotic arms require careful setup by surgical staff to maximize anatomical reach and avoid collisions. Furthermore, safety regulations prevent automatically driving robotic arms to this optimal positioning. We propose a Head-Mounted Display (HMD) based augmented reality (AR) guidance system for optimal surgical arm setup. In this case, the staff equipped with HMD aligns the robot with its planned virtual counterpart. The main challenge, however, is the perspective ambiguities hindering such collaborative robotic solution. To overcome this challenge, we introduce a novel registration concept for intuitive alignment of such AR content by providing a multi-view AR experience via reflective-AR displays that show the augmentations from multiple viewpoints. Using this system, operators can visualize different perspectives simultaneously while actively adjusting the pose to determine the registration transformation that most closely superimposes the virtual onto real. The experimental results demonstrate improvement in the interactive alignment of a virtual and real robot when using a reflective-AR display. We also present measurements from configuring a robotic manipulator in a simulated trocar placement surgery using the AR guidance methodology.

The use of Augmented Reality (AR) for navigation purposes has shown beneficial in assisting physicians during the performance of surgical procedures. These applications commonly require knowing the pose of surgical tools and patients to provide visual information that surgeons can use during the performance of the task. Existing medical-grade tracking systems use infrared cameras placed inside the Operating Room (OR) to identify retro-reflective markers attached to objects of interest and compute their pose. Some commercially available AR Head-Mounted Displays (HMDs) use similar cameras for self-localization, hand tracking, and estimating the objects' depth. This work presents a framework that uses the built-in cameras of AR HMDs to enable accurate tracking of retro-reflective markers without the need to integrate any additional electronics into the HMD. The proposed framework can simultaneously track multiple tools without having previous knowledge of their geometry and only requires establishing a local network between the headset and a workstation. Our results show that the tracking and detection of the markers can be achieved with an accuracy of 0.09 ± 0.06 mm on lateral translation, 0.42 ± 0.32 mm on longitudinal translation and 0.80 ± 0.39 • for rotations around the vertical axis. Furthermore, to showcase the relevance of the proposed framework, we evaluate the system's performance in the context of surgical procedures. This use case was designed to replicate the scenarios of k-wire insertions in orthopedic procedures. For evaluation, seven surgeons were provided with visual navigation and asked to perform 24 injections using the proposed framework. A second study with ten participants served to investigate the capabilities of the framework in the context of more general scenarios. Results from these studies provided comparable accuracy to those reported in the literature for AR-based navigation procedures.

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Three decades after the first set of work on Medical Augmented Reality (MAR) was presented to the international community, and ten years after the deployment of the first MAR solutions into operating rooms, its exact definition, basic components, systematic design, and validation still lack a detailed discussion. This paper defines the basic components of any Augmented Reality (AR) solution and extends them to exemplary Medical Augmented Reality Systems (MARS). We use some of the original MARS applications developed at the Chair for Computer Aided Medical Procedures and deployed into medical schools for teaching anatomy and into operating rooms for telemedicine and surgical guidance throughout the last decades to identify the corresponding basic components. In this regard, the paper is not discussing all past or existing solutions but only aims at defining the principle components and discussing the particular domain modeling for MAR and its design-development-validation process, and providing exemplary cases through the past in-house developments of such solutions.