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Proceedings Paper

Cone-beam CT of traumatic brain injury using statistical reconstruction with a post-artifact-correction noise model
Author(s): H. Dang; J. W. Stayman; A. Sisniega; J. Xu; W. Zbijewski; J. Yorkston; N. Aygun; V. Koliatsos; J. H. Siewerdsen
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Paper Abstract

Traumatic brain injury (TBI) is a major cause of death and disability. The current front-line imaging modality for TBI detection is CT, which reliably detects intracranial hemorrhage (fresh blood contrast 30-50 HU, size down to 1 mm) in non-contrast-enhanced exams. Compared to CT, flat-panel detector (FPD) cone-beam CT (CBCT) systems offer lower cost, greater portability, and smaller footprint suitable for point-of-care deployment. We are developing FPD-CBCT to facilitate TBI detection at the point-of-care such as in emergent, ambulance, sports, and military applications. However, current FPD-CBCT systems generally face challenges in low-contrast, soft-tissue imaging. Model-based reconstruction can improve image quality in soft-tissue imaging compared to conventional filtered back-projection (FBP) by leveraging high-fidelity forward model and sophisticated regularization. In FPD-CBCT TBI imaging, measurement noise characteristics undergo substantial change following artifact correction, resulting in non-negligible noise amplification. In this work, we extend the penalized weighted least-squares (PWLS) image reconstruction to include the two dominant artifact corrections (scatter and beam hardening) in FPD-CBCT TBI imaging by correctly modeling the variance change following each correction. Experiments were performed on a CBCT test-bench using an anthropomorphic phantom emulating intra-parenchymal hemorrhage in acute TBI, and the proposed method demonstrated an improvement in blood-brain contrast-to-noise ratio (CNR = 14.2) compared to FBP (CNR = 9.6) and PWLS using conventional weights (CNR = 11.6) at fixed spatial resolution (1 mm edge-spread width at the target contrast). The results support the hypothesis that FPD-CBCT can fulfill the image quality requirements for reliable TBI detection, using high-fidelity artifact correction and statistical reconstruction with accurate post-artifact-correction noise models.

Paper Details

Date Published: 18 March 2015
PDF: 7 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 941207 (18 March 2015); doi: 10.1117/12.2082075
Show Author Affiliations
H. Dang, Johns Hopkins Univ. (United States)
J. W. Stayman, Johns Hopkins Univ. (United States)
A. Sisniega, Johns Hopkins Univ. (United States)
J. Xu, Johns Hopkins Univ. (United States)
W. Zbijewski, Johns Hopkins Univ. (United States)
J. Yorkston, Carestream Health, Inc. (United States)
N. Aygun, Johns Hopkins Univ. (United States)
V. Koliatsos, Johns Hopkins Univ. (United States)
J. H. Siewerdsen, Johns Hopkins Univ. (United States)


Published in SPIE Proceedings Vol. 9412:
Medical Imaging 2015: Physics of Medical Imaging
Christoph Hoeschen; Despina Kontos, Editor(s)

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