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Proceedings Paper

Image-based motion compensation for high-resolution extremities cone-beam CT
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Paper Abstract

Purpose: Cone-beam CT (CBCT) of the extremities provides high spatial resolution, but its quantitative accuracy may be challenged by involuntary sub-mm patient motion that cannot be eliminated with simple means of external immobilization. We investigate a two-step iterative motion compensation based on a multi-component metric of image sharpness. Methods: Motion is considered with respect to locally rigid motion within a particular region of interest, and the method supports application to multiple locally rigid regions. Motion is estimated by maximizing a cost function with three components: a gradient metric encouraging image sharpness, an entropy term that favors high contrast and penalizes streaks, and a penalty term encouraging smooth motion. Motion compensation involved initial coarse estimation of gross motion followed by estimation of fine-scale displacements using high resolution reconstructions. The method was evaluated in simulations with synthetic motion (1–4 mm) applied to a wrist volume obtained on a CMOS-based CBCT testbench. Structural similarity index (SSIM) quantified the agreement between motion-compensated and static data. The algorithm was also tested on a motion contaminated patient scan from dedicated extremities CBCT. Results: Excellent correction was achieved for the investigated range of displacements, indicated by good visual agreement with the static data. 10-15% improvement in SSIM was attained for 2-4 mm motions. The compensation was robust against increasing motion (4% decrease in SSIM across the investigated range, compared to 14% with no compensation). Consistent performance was achieved across a range of noise levels. Significant mitigation of artifacts was shown in patient data. Conclusion: The results indicate feasibility of image-based motion correction in extremities CBCT without the need for a priori motion models, external trackers, or fiducials.

Paper Details

Date Published: 22 March 2016
PDF: 7 pages
Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97830K (22 March 2016); doi: 10.1117/12.2217243
Show Author Affiliations
A. Sisniega, Johns Hopkins Univ. (United States)
J. W. Stayman, Johns Hopkins Univ. (United States)
Q. Cao, Johns Hopkins Univ. (United States)
J. Yorkston, Carestream Health, Inc. (United States)
J. H. Siewerdsen, Johns Hopkins Univ. (United States)
W. Zbijewski, Johns Hopkins Univ. (United States)


Published in SPIE Proceedings Vol. 9783:
Medical Imaging 2016: Physics of Medical Imaging
Despina Kontos; Thomas G. Flohr, Editor(s)

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