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On-patient see-through augmented reality based on visual SLAM

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

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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Acknowledgments

This work is supported by the Direccíon General de Investigacíon Centífica y Técnica of Spain under Project RT-SLAM DPI2015-67275-P.

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Correspondence to Nader Mahmoud.

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The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Additionally, all applicable international, national and/or institutional guidelines for the care and use of animals were followed.

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Informed consent was obtained from all individual participants included in the study.

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Mahmoud, N., Grasa, Ó.G., Nicolau, S.A. et al. On-patient see-through augmented reality based on visual SLAM. Int J CARS 12, 1–11 (2017). https://doi.org/10.1007/s11548-016-1444-x

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  • DOI: https://doi.org/10.1007/s11548-016-1444-x

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