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Proceedings Paper

Noise properties of low-dose x-ray CT sinogram data in radon space
Author(s): Jing Wang; Hongbing Lu; Zhengrong Liang; Daria Eremina; Guangxiang Zhang; Su Wang; John Chen; James Manzione
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Paper Abstract

Computed tomography (CT) has been well established as a diagnostic tool through hardware optimization and sophisticated data calibration. For screening purposes, the associated X-ray exposure risk must be minimized. An effective way to minimize the risk is to deliver fewer X-rays to the subject or lower the mAs parameter in data acquisition. This will increase the data noise. This work aims to study the noise property of the calibrated or preprocessed sinogram data in Radon space as the mAs level decreases. An anthropomorphic torso phantom was scanned repeatedly by a commercial CT imager at five different mAs levels from 100 down to 17 (the lowest value provided by the scanner). The preprocessed sinogram datasets were extracted from the CT scanner to a laboratory computer for noise analysis. The repeated measurements at each mAs level were used to test the normality of the repeatedly measured samples for each data channel using the Shapiro-Wilk statistical test merit. We further studied the probability distribution of the repeated measures. Most importantly, we validated a theoretical relationship between the sample mean and variance at each channel. It is our intention that the statistical test and particularly the relationship between the first and second statistical moments will improve low-dose CT image reconstruction for screening applications.

Paper Details

Date Published: 18 March 2008
PDF: 10 pages
Proc. SPIE 6913, Medical Imaging 2008: Physics of Medical Imaging, 69131M (18 March 2008); doi: 10.1117/12.771153
Show Author Affiliations
Jing Wang, SUNY (United States)
Hongbing Lu, Fourth Military Medical Univ. (China)
Zhengrong Liang, SUNY (United States)
Daria Eremina, SUNY (United States)
Guangxiang Zhang, SUNY (United States)
Su Wang, SUNY (United States)
John Chen, SUNY (United States)
James Manzione, SUNY (United States)

Published in SPIE Proceedings Vol. 6913:
Medical Imaging 2008: Physics of Medical Imaging
Jiang Hsieh; Ehsan Samei, Editor(s)

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