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16 March 2020 Accuracy study of smartglasses/smartphone AR systems for percutaneous needle interventions
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Purpose: This study aims to investigate the accuracy of a cross platform augmented reality (AR) system for percutaneous needle interventions irrespective of operator error. In particular, we study the effect of the relative position and orientation of the AR device and the marker, the location of the target, and the angle of needle on the overlay accuracy. Method: A needle guidance AR platform developed using Unity and Vuforia SDK platforms was used to display a planned needle trajectory for targets via mobile and wearable devices. To evaluate the system accuracy, a custom phantom embedded with metal fiducial markers and an adjustable needle guide was designed to mimic different relative position and orientation scenarios of the smart device and the marker. After segmenting images of CT-visible fiducial markers as well as different needle trajectories, error was defined by comparing them to the corresponding augmented target/needle trajectory projected by smartphone and smartglasses devices. Results: The augmentation error for targets and needle trajectories were reported as a function of marker position and orientation, as well as the location of the targets. Overall, the image overlay error for needle trajectory was 0.28±0.32° (Max = 0.856°) and 0.41±0.23° (Max = 0.805°) using the iPhone and HoloLens glasses, respectively. The overall image overlay error for targets was 1.75±0.59 mm for iPhone, and 1.74±0.86 mm for HoloLens. Conclusions: The image overlay error caused by different sources can be quantified for different AR devices.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Reza Seifabadi, Ming Li, Dilara Long, Sheng Xu, and Bradford J. Wood "Accuracy study of smartglasses/smartphone AR systems for percutaneous needle interventions", Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 113150V (16 March 2020);

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