Co-localized augmented human and X-ray observers in collaborative surgical ecosystem

Journal article


Publication Details

Author(s): Fotouhi J, Unberath M, Song T, Hajek J, Lee SC, Bier B, Maier A, Osgood G, Armand M, Navab N
Journal: International Journal of Computer Assisted Radiology and Surgery
Publication year: 2019
ISSN: 1861-6410
eISSN: 1861-6429


Abstract

Purpose: Image-guided percutaneous interventions are safer alternatives to conventional orthopedic and trauma surgeries. To advance surgical tools in complex bony structures during these procedures with confidence, a large number of images is acquired. While image-guidance is the de facto standard to guarantee acceptable outcome, when these images are presented on monitors far from the surgical site the information content cannot be associated easily with the 3D patient anatomy. Methods: In this article, we propose a collaborative augmented reality (AR) surgical ecosystem to jointly co-localize the C-arm X-ray and surgeon viewer. The technical contributions of this work include (1) joint calibration of a visual tracker on a C-arm scanner and its X-ray source via a hand-eye calibration strategy, and (2) inside-out co-localization of human and X-ray observers in shared tracking and augmentation environments using vision-based simultaneous localization and mapping. Results: We present a thorough evaluation of the hand-eye calibration procedure. Results suggest convergence when using 50 pose pairs or more. The mean translation and rotation errors at convergence are 5.7 mm and 0. 26 , respectively. Further, user-in-the-loop studies were conducted to estimate the end-to-end target augmentation error. The mean distance between landmarks in real and virtual environment was 10.8 mm. Conclusions: The proposed AR solution provides a shared augmented experience between the human and X-ray viewer. The collaborative surgical AR system has the potential to simplify hand-eye coordination for surgeons or intuitively inform C-arm technologists for prospective X-ray view-point planning.


FAU Authors / FAU Editors

Bier, Bastian
Lehrstuhl für Informatik 5 (Mustererkennung)
Maier, Andreas Prof. Dr.-Ing.
Lehrstuhl für Informatik 5 (Mustererkennung)


External institutions with authors

Johns Hopkins Hospital
Johns Hopkins University


How to cite

APA:
Fotouhi, J., Unberath, M., Song, T., Hajek, J., Lee, S.C., Bier, B.,... Navab, N. (2019). Co-localized augmented human and X-ray observers in collaborative surgical ecosystem. International Journal of Computer Assisted Radiology and Surgery. https://dx.doi.org/10.1007/s11548-019-02035-8

MLA:
Fotouhi, Javad, et al. "Co-localized augmented human and X-ray observers in collaborative surgical ecosystem." International Journal of Computer Assisted Radiology and Surgery (2019).

BibTeX: 

Last updated on 2019-07-08 at 06:53