The global noise level provides an accurate, robust, and automated method to measure CT noise in clinical examinations for quality assurance programs. The significant difference in noise across scanner models indicates the unexploited potential to efficiently assess and subsequently improve protocol consistency. Combined with other automated characterization of imaging performance (e.g., dose monitoring), the global noise level may offer a promising platform for the standardization and optimization of CT protocols.
This paper reports on the methodology and materials used to construct anthropomorphic phantoms for use in dosimetry studies, improving on methods and materials previously described by Jones et al. [Med Phys. 2006;33(9):3274–82]. To date, the methodology described has been successfully used to create a series of three different adult phantoms at the University of Florida (UF). All phantoms were constructed in 5 mm transverse slices using materials designed to mimic human tissue at diagnostic photon energies: soft tissue‐equivalent substitute (STES), lung tissue‐equivalent substitute (LTES), and bone tissue‐equivalent substitute (BTES). While the formulation for BTES remains unchanged from the previous epoxy resin compound developed by Jones et al. [Med Phys. 2003;30(8):2072—81], both the STES and LTES were redesigned utilizing a urethane‐based compound which forms a pliable tissue‐equivalent material. These urethane‐based materials were chosen in part for improved phantom durability and easier accommodation of real‐time dosimeters. The production process has also been streamlined with the use of an automated machining system to create molds for the phantom slices from bitmap images based on the original segmented computed tomography (CT) datasets. Information regarding the new tissue‐equivalent materials, as well as images of the construction process and completed phantom, are included.PACS number: 87.53.Bn
Matching image appearance in terms of resolution, noise magnitude, and noise texture provides a quantitative and reproducible strategy to improve consistency in image quality among different CT scanners and reconstructions.
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