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Proceedings Paper

Image-based deformable motion compensation for interventional cone-beam CT
Author(s): A. Sisniega; S. Capostagno; W. Zbijewski; C. R. Weiss; T. Ehtiati; J. H. Siewerdsen
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Paper Abstract

Purpose: Interventional cone-beam CT (CBCT) is used for 3D guidance in interventional radiology (IR) procedures in the abdomen, with extended presence in trans-arterial chemoembolization (TACE) interventions for liver cancer. Image quality in this scenario is challenged by complex motion of soft-tissue abdominal structures, and by long acquisition times. We propose an image-based approach to estimate complex deformable motion through a combination of locally rigid motion trajectories. Methods: Deformable motion is estimated by minimizing a multi-region autofocus cost function. Motion is considered locally rigid for each region of interest (ROI) and the deformable motion field is obtained through spatial spline-based interpolation of the local trajectories. The multi-component cost function includes two regularization terms; one to penalize abrupt temporal transitions, and another to penalize abrupt spatial changes in the trajectory. Performance of deformable motion compensation was assessed in simulation studies with a digital abdomen phantom featuring a motion-induced deformable liver in static surrounding anatomy. Spherical inserts (4 – 12 mm diameter, -100 – 100 HU contrast) were placed in the liver. Image quality was evaluated by structural similarity (SSIM) with the static image as reference. Results: Motion compensated liver images showed better delineation of structure boundaries and recovery of distorted spherical shapes compared to their motion-corrupted counterparts. Consistent increase in SSIM was observed after motion compensation for the range of motion amplitudes studied (4 mm to 10 mm), showing 11% and 26% greater SSIM for 4 mm and 10 mm motion, respectively. Conclusion: The results indicate feasibility of image-based deformable motion compensation in soft-tissue abdominal CBCT imaging.

Paper Details

Date Published: 1 March 2019
PDF: 6 pages
Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109481O (1 March 2019); doi: 10.1117/12.2513446
Show Author Affiliations
A. Sisniega, Johns Hopkins Univ. (United States)
S. Capostagno, Johns Hopkins Univ. (United States)
W. Zbijewski, Johns Hopkins Univ. (United States)
C. R. Weiss, Johns Hopkins Univ. (United States)
T. Ehtiati, Siemens Medical Solutions (United States)
J. H. Siewerdsen, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 10948:
Medical Imaging 2019: Physics of Medical Imaging
Taly Gilat Schmidt; Guang-Hong Chen; Hilde Bosmans, Editor(s)

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