Quantification and homogenization of image noise between two CT scanner models.

Feedback from radiologists indicated that differences in image appearance and noise impeded reading of post-contrast computed tomography (CT) scans from an updated CT scanner that was recently added to a fleet of existing scanners from the same vendor, despite using identically named reconstruction algorithms. The goals of this work were to quantify and possibly standardize image quality on the new and an existing scanner using phantom images. Three months of daily quality control images were analyzed to determine the mean CT number and noise magnitude in a water phantom. Next, subtraction images from the uniformity section of an American College of Radiology CT phantom were used to generate noise power spectra for both scanners. Then, a semi-anthropomorphic liver phantom was imaged with both scanners in triplicate using identical body protocols to quantify differences CT number and noise magnitude. Finally, the scanner dependence of CT number and noise magnitude on material attenuation was quantified using a multi-energy CT phantom with 15 material inserts. Significant differences between scanners were determined using a paired or Welch's t test as appropriate. In daily quality control images, the new scanner exhibited slightly higher CT number (0.697 vs. 0.412, P < 0.001, n = 85) and slightly lower noise magnitude (4.85 vs. 4.94, P < 0.001, n = 85). Measured NPS was not significantly different between the existing and new scanners. Interestingly, it was observed that the noise magnitude from the new scanner increased with increasing material attenuation in both the liver (P = 0.008) and multi-energy (P < 0.001) phantoms. Using an alternate reconstruction algorithm with the new scanner eliminated this deviation at high material attenuations. While standard noise evaluation in a water phantom was unable to discern differences between the scanners, more comprehensive testing with higher attenuation materials allowed for the characterization and homogenization of image quality.

Noise Power Characteristics of a Micro-Computed Tomography System.

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.