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NPS characterization and evaluation of a cone beam CT breast imaging system. | LitMetric

AI Article Synopsis

Article Abstract

The Noise Power Spectrum (NPS) is a function that yields information about the spatial frequency composition of noise in images obtained by a system. It is evaluated by calculating the absolute value squared of the noise image and normalizing it with respect to the voxel and matrix sizes. Consequently, the NPS has been one of the physical characteristics that is commonly used to quantitatively measure the physical performance of a system. In this article, we evaluated the NPS of a Cone Beam CT Breast Imaging system by considering the following factors. First, we evaluated its symmetry around the x- and y-axis along with the influence of the cone angle and the matrix size on the NPS. Then, an analytical curve was suggested to best represent the NPS. Second, we analyzed the influence on the NPS of a set of seven parameters, namely the pixel size, exposure level, kVp value, number of projections acquired, voxel size, back projection filter, and the reconstruction algorithm employed. In addition, since the breast induced scattering in the image, we investigated the effect of the scattering-correction algorithm used in this system. Finally, we evaluated the uniformity of the NPS as a function of z with the matrix center located at {r = 0 mm}. The results demonstrate that the proposed curve is an ideal candidate that best represents the NPS. Hence, two parameters, the amplitude (A) and the width (sigma), can be used to characterize the curve. The results also demonstrate that the voxel size and the cone angle are the only two parameters investigated in this study that do not affect the NPS. On the other hand, the matrix and pixel sizes, the back-projection filter and the reconstruction algorithm, the exposure level and the scattering correction, all influence the NPS. Finally, the results of the last part of this investigation suggest that this imaging system does not have a 3D isotropic noise distribution along the z-axis; yielding less noisy images at around z = 0.00 m and z = 80 mm.

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http://dx.doi.org/10.3233/XST-2009-0213DOI Listing

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