Noise Power Characteristics of a Micro-Computed Tomography System
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Updated: Mar 14, 2026

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Muhammad U Ghani1, Liqiang Ren, Molly Wong
1From the *Center for Biomedical Engineering and School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK; †Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX; and ‡Department of Radiation, Massachusetts General Hospital, Boston, MA.
Objective:
The aim of this study was to investigate the noise power properties of a micro-computed tomography (micro-CT) system under different operating conditions.
Methods:
A commercial micro-CT was used in the study that used a flat panel detector with a 127-μm-pixel pitch and a micro-focus x-ray tube. Conical tubes of various diameters were used under different acquisition conditions. Multidimensional noise power spectrums were used as a metric to investigate the noise properties of the system. Noise power spectrum was calculated from the difference data generated by subtraction of 2 identical scans. The noise properties with respect to various parameters that include the impact of number of projections, x-ray spectra, milliampere-second, slice location, object diameter, voxel size, geometric magnification (M), back-projection filters, and reconstruction magnification (Mrecon) were studied.
Results:
At a same isocentric exposure rate of 270 mR/s, the noise power was much lower for the image reconstructed with 3672 views (122 seconds) as compared with the 511 views (17 seconds), whereas at a fixed isocentric exposure of 4600 mR, the noise power levels were almost similar. Image noise with a 50-kV beam was higher as compared with the 90-kV beam at a same isocentric exposure. Image noise from a 16-mm-diameter conical tube was much lower as compared with the 28- and 56-mm tubes under identical isocentric exposures. The choice of back-projection filter influences noise power spectrum curves in terms of width and amplitudes. Reconstruction magnification applied during the reconstruction process increased the noise power at lower spatial frequencies but reduced the noise power at higher spatial frequencies. It can be established that, for small details corresponding to high spatial frequencies, reconstruction magnification can provide an improved signal-to-noise ratio. At all spatial frequencies, the in-plane images had lower noise power levels as compared with the z-plane images.
Conclusions:
The noise power properties investigated in this study provide important image quality references for refined cone beam system development, optimization, and operations.
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