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On-patient See-through Augmented Reality Based on Visual SLAM

Overview
Journal Int J Comput Assist Radiol Surg
Publisher Springer
Specialties General Surgery
Radiology
Date 2016 Jul 5
PMID 27376720
Citations 7
Authors
Nader Mahmoud
Oscar G Grasa
Stephane A Nicolau
Christophe Doignon
Luc Soler
Jacques Marescaux
J M M Montiel
Affiliations
Soon will be listed here.
Abstract

Purpose: An augmented reality system to visualize a 3D preoperative anatomical model on intra-operative patient is proposed. The hardware requirement is commercial tablet-PC equipped with a camera. Thus, no external tracking device nor artificial landmarks on the patient are required.

Methods: We resort to visual SLAM to provide markerless real-time tablet-PC camera location with respect to the patient. The preoperative model is registered with respect to the patient through 4-6 anchor points. The anchors correspond to anatomical references selected on the tablet-PC screen at the beginning of the procedure.

Results: Accurate and real-time preoperative model alignment (approximately 5-mm mean FRE and TRE) was achieved, even when anchors were not visible in the current field of view. The system has been experimentally validated on human volunteers, in vivo pigs and a phantom.

Conclusions: The proposed system can be smoothly integrated into the surgical workflow because it: (1) operates in real time, (2) requires minimal additional hardware only a tablet-PC with camera, (3) is robust to occlusion, (4) requires minimal interaction from the medical staff.

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Image Overlay Surgery Based on Augmented Reality: A Systematic Review.

Perez-Pachon L, Poyade M, Lowe T, Groning F Adv Exp Med Biol. 2020; 1260:175-195.

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Accuracy assessment for the co-registration between optical and VIVE head-mounted display tracking.

Groves L, Carnahan P, Allen D, Adam R, Peters T, Chen E Int J Comput Assist Radiol Surg. 2019; 14(7):1207-1215.

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Augmented reality-based electrode guidance system for reliable electroencephalography.

Song C, Jeon S, Lee S, Ha H, Kim J, Hong J Biomed Eng Online. 2018; 17(1):64.

PMID: 29793498 PMC: 5968572. DOI: 10.1186/s12938-018-0500-x.

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