19 March 2014 Noise performance of statistical model based iterative reconstruction in clinical CT systems
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Abstract
The statistical model based iterative reconstruction (MBIR) method has been introduced to clinical CT systems. Due to the nonlinearity of this method, the noise characteristics of MBIR are expected to differ from those of filtered backprojection (FBP). This paper reports an experimental characterization of the noise performance of MBIR equipped on several state-of-the-art clinical CT scanners at our institution. The thoracic section of an anthropomorphic phantom was scanned 50 times to generate image ensembles for noise analysis. Noise power spectra (NPS) and noise standard deviation maps were assessed locally at different anatomical locations. It was found that MBIR lead to significant reduction in noise magnitude and improvement in noise spatial uniformity when compared with FBP. Meanwhile, MBIR shifted the NPS of the reconstructed CT images towards lower frequencies along both the axial and the z frequency axes. This effect was confirmed by a relaxed slice thicknesstradeoff relationship shown in our experimental data. The unique noise characteristics of MBIR imply that extra effort must be made to optimize CT scanning parameters for MBIR to maximize its potential clinical benefits.
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Ke Li, Jie Tang, Guang-Hong Chen, "Noise performance of statistical model based iterative reconstruction in clinical CT systems", Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90335J (19 March 2014); doi: 10.1117/12.2043974; https://doi.org/10.1117/12.2043974
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