
Proceedings Paper
Self-calibration of cone-beam CT geometry using 3D-2D image registration: development and application to tasked-based imaging with a robotic C-armFormat | Member Price | Non-Member Price |
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Paper Abstract
Purpose: Robotic C-arm systems are capable of general noncircular orbits whose trajectories can be driven by the particular imaging task. However obtaining accurate calibrations for reconstruction in such geometries can be a challenging problem. This work proposes a method to perform a unique geometric calibration of an arbitrary C-arm orbit by registering 2D projections to a previously acquired 3D image to determine the transformation parameters representing the system geometry.
Methods: Experiments involved a cone-beam CT (CBCT) bench system, a robotic C-arm, and three phantoms. A robust 3D-2D registration process was used to compute the 9 degree of freedom (DOF) transformation between each projection and an existing 3D image by maximizing normalized gradient information with a digitally reconstructed radiograph (DRR) of the 3D volume. The quality of the resulting “self-calibration” was evaluated in terms of the agreement with an established calibration method using a BB phantom as well as image quality in the resulting CBCT reconstruction.
Results: The self-calibration yielded CBCT images without significant difference in spatial resolution from the standard (“true”) calibration methods (p-value >0.05 for all three phantoms), and the differences between CBCT images reconstructed using the “self” and “true” calibration methods were on the order of 10-3 mm-1. Maximum error in magnification was 3.2%, and back-projection ray placement was within 0.5 mm.
Conclusion: The proposed geometric “self” calibration provides a means for 3D imaging on general noncircular orbits in CBCT systems for which a geometric calibration is either not available or not reproducible. The method forms the basis of advanced “task-based” 3D imaging methods now in development for robotic C-arms.
Paper Details
Date Published: 18 March 2015
PDF: 7 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 94151D (18 March 2015); doi: 10.1117/12.2082538
Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster III; Ziv R. Yaniv, Editor(s)
PDF: 7 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 94151D (18 March 2015); doi: 10.1117/12.2082538
Show Author Affiliations
S. Ouadah, Johns Hopkins Univ. (United States)
J. W. Stayman, Johns Hopkins Univ. (United States)
G. Gang, Johns Hopkins Univ. (United States)
J. W. Stayman, Johns Hopkins Univ. (United States)
G. Gang, Johns Hopkins Univ. (United States)
A. Uneri, Johns Hopkins Univ. (United States)
T. Ehtiati, Siemens Healthcare (Germany)
J. H. Siewerdsen, Johns Hopkins Univ. (United States)
T. Ehtiati, Siemens Healthcare (Germany)
J. H. Siewerdsen, Johns Hopkins Univ. (United States)
Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster III; Ziv R. Yaniv, Editor(s)
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