C-arm pose estimation and navigation in surgeries for augmented reality application

Hosseinian S, Arefi H, Navab N (2019)

Publication Type: Conference contribution

Publication year: 2019

Publisher: International Society for Photogrammetry and Remote Sensing

Book Volume: 42

Pages Range: 497-505

Conference Proceedings Title: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Event location: Karaj, IRN

DOI: 10.5194/isprs-archives-XLII-4-W18-497-2019

Abstract

C-arm X-ray imaging systems are widely applied in surgeries. Overlaying X-ray with optical images during the surgery has been shown to be an efficient approach. Moreover, overlaying needed data from different modalities in an augmented reality (AR) manner can improve the accuracy of surgical procedures, decrease the variability of surgical outcomes, reduce trauma to the critical structures, increase the reproducibility of surgeons' performance, and reduce radiation exposure. C-Arm geometric calibration and recovering the C-arm pose are essential for surgical navigation and AR applications in operating rooms. Therefore, in this paper, existing researches for calibration and pose estimation of C-arm devices in surgical AR applications are evaluated from photogrammetric point of view. Then, a proposed marker-based method for C-arm pose estimation is introduced. For this purpose, a marker is designed to facilitate tracking and pose estimation in mixed reality based on golden section principle, and perspective invariants such as cross-ratios, collinearity, and intersection. Moreover, a procedure is also proposed for fast determination of these fiducial markers. The experiments show benefits of such a structure which has a limited occlusion with consistency to different conditions such as narrow field of view and at the same time, even in images with high projectivity. It also results that the distortion correction step is important and the effect of distortion of X-ray images can cause inconsistency in the perspective invariants.

Involved external institutions

University of Tehran IR Iran, Islamic Republic of (IR) Technische Universität München (TUM) DE Germany (DE)

How to cite

APA:

Hosseinian, S., Arefi, H., & Navab, N. (2019). C-arm pose estimation and navigation in surgeries for augmented reality application. In H. Arefi, M. Saadat Seresht (Eds.), International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (pp. 497-505). Karaj, IRN: International Society for Photogrammetry and Remote Sensing.

MLA:

Hosseinian, S., H. Arefi, and N. Navab. "C-arm pose estimation and navigation in surgeries for augmented reality application." Proceedings of the ISPRS International GeoSpatial Conference 2019, Joint Conferences of 5th Sensors and Models in Photogrammetry and Remote Sensing, SMPR 2019 and 3rd Geospatial Information Research, GI Research 2019, Karaj, IRN Ed. H. Arefi, M. Saadat Seresht, International Society for Photogrammetry and Remote Sensing, 2019. 497-505.

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