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Proceedings Paper

Clinical study of soft-tissue contrast resolution in cone-beam CT of the head using multi-resolution PWLS with multi-motion correction and an electronic noise model
Author(s): P. Wu; A. Sisniega; J. W. Stayman; W. Zbijewski; D. Foos; X. Wang; N. Aygun; R. Stevens; J. H. Siewerdsen
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Paper Abstract

Purpose: Improving soft-tissue contrast resolution beyond the capability of current cone-beam CT (CBCT) systems is essential to a growing range of image guidance and diagnostic imaging scenarios. We present a framework for CBCT model-based image reconstruction (MBIR) combining artifact corrections with multi-resolution reconstruction and multiregion motion compensation and apply the method for the first time in a clinical study of CBCT for high-quality imaging of head injury. Methods: A CBCT prototype was developed for mobile point-of-care imaging in the neuro-critical care unit (NCCU). Projection data were processed via poly-energetic gain correction and an artifacts correction pipeline treating scatter, beam hardening, and motion compensation. The scatter correction was modified to use a penalized weighted least-squares (PWLS) image in the Monte-Carlo (MC) object model for better uniformity in truncated data. The PWLS method included: (1) multi-resolution reconstruction to mitigate lateral truncation from the head-holder; (2) multi-motion compensation allowing separate motion of the head and head-holder; and (3) modified statistical weights to account for electronics noise and fluence modulation by the bowtie filter. Imaging performance was evaluated in simulation and in the first clinical study (N = 54 patients) conducted with the system. Results: Using a PWLS object model in the final iteration of the MC scatter estimate improved image uniformity by 40.4% for truncated datasets. The multi-resolution, multi-motion PWLS method greatly reduced streak artifacts and nonuniformity both in simulation (RMSE reduced by 65.5%) and in the clinical study (visual image quality assessed by a neuroradiologist). Up to 15% reduction in variance was achieved using statistical weights modified according to a model for electronic noise from the detector. Each component was important for improved contrast resolution in the patient data. Conclusion: An integrated pipeline for artifacts correction and PWLS reconstruction mitigated artifacts and noise to a level supporting visualization of low-contrast brain lesions and warranting future studies of diagnostic performance in the NCCU.

Paper Details

Date Published: 28 May 2019
PDF: 5 pages
Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 110720B (28 May 2019); doi: 10.1117/12.2534887
Show Author Affiliations
P. Wu, Johns Hopkins Univ. (United States)
A. Sisniega, Johns Hopkins Univ. (United States)
J. W. Stayman, Johns Hopkins Univ. (United States)
W. Zbijewski, Johns Hopkins Univ. (United States)
D. Foos, Carestream Health (United States)
X. Wang, Carestream Health (United States)
N. Aygun, Johns Hopkins Univ. (United States)
R. Stevens, Johns Hopkins Univ. (United States)
J. H. Siewerdsen, Johns Hopkins Univ. (United States)


Published in SPIE Proceedings Vol. 11072:
15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
Samuel Matej; Scott D. Metzler, Editor(s)

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