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Proceedings Paper

Noise study on cone-beam CT FDK image reconstruction by improved area-simulating-volume technique
Author(s): Yan Liu; Jin Wang; Hao Zhang; Yi Fan; Zhengrong Liang
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Paper Abstract

Previous studies have reported that the volume-weighting technique has advantages over the linear interpolation technique for cone-beam computed tomography (CBCT) image reconstruction. However, directly calculating the intersecting volume between the pencil beam X-ray and the object is a challenge due to the computational complexity. Inspired by previous works in area-simulating volume (ASV) technique for 3D positron emission tomography, we proposed an improved ASV (IASV) technique, which can fast calculate the geometric probability of the intersection between the pencil beam and the object. In order to show the improvements of using IASV technique in volumeweighting based Feldkamp–Davis–Kress (VW-FDK) algorithm compared to the conventional linear interpolation technique based FDK algorithm (LI-FDK), the variances images from both theoretical prediction and empirical determination are described basing on the assumption of the uncorrelated and stationary noise for each detector bin. In digital phantom study, both of the theoretically predicted variance images and the empirically determined variance images concurred and demonstrated that the VW-FDK algorithm can result in uniformly distributed noise across the FOV. In the physical phantom study, the performance enhancements by the VW-FDK algorithm were quantitatively evaluated by the contrast-noise-ratio (CNR) merit. The CNR values from the VW-FDK result were about 40% higher than the conventional LI-FDK result. Therefore it can be concluded that the VW-FDK algorithm can efficiently address the non-uniformity noise and suppress noise level of the reconstructed images.

Paper Details

Date Published: 19 March 2014
PDF: 7 pages
Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 903339 (19 March 2014); doi: 10.1117/12.2043721
Show Author Affiliations
Yan Liu, Stony Brook Univ. (United States)
Jin Wang, The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)
Hao Zhang, Stony Brook Univ. (United States)
Yi Fan, Stony Brook Univ. (United States)
Zhengrong Liang, Stony Brook Univ. (United States)


Published in SPIE Proceedings Vol. 9033:
Medical Imaging 2014: Physics of Medical Imaging
Bruce R. Whiting; Christoph Hoeschen, Editor(s)

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