Paper
3 March 2012 Non-uniform noise spatial distribution in CT myocardial perfusion and a potential solution: statistical image reconstruction
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Abstract
Myocardial perfusion scans are an important tool in the assessment of myocardial viability following an infarction. Cardiac perfusion analysis using CT datasets is limited by the presence of so-called partial scan artifacts. These artifacts are due to variations in beam hardening and scatter between different short-scan angular ranges. In this research, another angular range dependent effect is investigated: non-uniform noise spatial distribution. Images reconstructed using filtered backprojection (FBP) are subject to this effect. Statistical image reconstruction (SIR) is proposed as a potential solution. A numerical phantom with added Poisson noise was simulated and two swines were scanned in vivo to study the effect of FBP and SIR on the spatial uniformity of the noise distribution. It was demonstrated that images reconstructed using FBP often show variations in noise on the order of 50% between different time frames. This variation is mitigated to about 10% using SIR. The noise level is also reduced by a factor of 2 in SIR images. Finally, it is demonstrated that the measurement of quantitative perfusion metrics are generally more accurate when SIR is used instead of FBP.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pascal Thériault Lauzier, Jie Tang, and Guang-Hong Chen "Non-uniform noise spatial distribution in CT myocardial perfusion and a potential solution: statistical image reconstruction", Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 831338 (3 March 2012); https://doi.org/10.1117/12.911554
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Cited by 3 scholarly publications.
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KEYWORDS
In vivo imaging

Image restoration

Computed tomography

Image filtering

Reconstruction algorithms

Blood

Phase modulation

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