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Proceedings Paper

Smartglasses/smartphone needle guidance AR system for transperineal prostate procedures
Author(s): Ming Li; Sheng Xu; Dumitru Mazilu; Baris Turkbey; Bradford J. Wood
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Paper Abstract

In transperineal prostate biopsy or ablation, a grid-template is typically used to guide the needle. The guidance method has limited positioning resolution and lack of needle angulation selections that are referenced to ultrasound imaging or TRUS-MRI fusion targets. To overcome the limitation, a novel augmented reality (AR) system that use smart see-through glasses and smartphone as a needle guidance device for transperineal prostate procedure was developed. The AR system is comprised of a MRI/CT scanner, a pre-procedural image analysis and visualization software, AR devices (smart-glasses, smartphone), a newly-developed AR app, as well as a local network. The AR app displays the lesion and planned needle trajectory, which are derived from the pre-procedural images, on the AR devices. A special designed image marker frame that affixed to the patient’s perineum was used to track the pre-procedural image with the AR devices. The displayed needle plan was always referenced to the patient and remains independent from the position and orientation of the devices. Multiple devices can be used simultaneously and communicate via a local network. We evaluated the AR system accuracy with iPhone and R-7 glasses in a phantom study. The image overlay accuracy was 0.58±0.43o and 1.62±1.52o in iPhone and R-7 glasses respectively. The accuracy of iPhone guidance was 1.9±0.97 mm (lateral) and 1.0±0.5 mm (in-direction), the accuracy of R-7 guidance was 2.8±1.4mm (lateral) and 2.3±1.5mm (indirection). AR system using smart-glasses and smartphone can provide accurate needle guidance and see-through-the-skin display for needle based transperineal prostate interventions like biopsy and ablation.

Paper Details

Date Published: 8 March 2019
PDF: 6 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109510Z (8 March 2019); doi: 10.1117/12.2512250
Show Author Affiliations
Ming Li, National Institutes of Health (United States)
Sheng Xu, National Institutes of Health (United States)
Dumitru Mazilu, National Institutes of Health (United States)
Baris Turkbey, National Institutes of Health (United States)
Bradford J. Wood, National Institutes of Health (United States)

Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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