AI Article Synopsis

  • The paper presents a method for assessing x-ray beam properties using both experimental and modeled data with a small-animal spectral scanner.
  • Key measurements include the shape of the beam profile, angular offsets, and differences in photon counts between experimental and modeled data.
  • The method demonstrates high precision, with minimal count errors and variations, and can identify system performance issues, ultimately improving the reliability and accuracy of spectral CT imaging.

Article Abstract

In this paper, we present a method that uses a combination of experimental and modeled data to assess properties of x-ray beam measured using a small-animal spectral scanner. The spatial properties of the beam profile are characterized by beam profile shape, the angular offset along the rotational axis, and the photon count difference between experimental and modeled data at the central beam axis. Temporal stability of the beam profile is assessed by measuring intra- and interscan count variations. The beam profile assessment method was evaluated on several spectral CT scanners equipped with Medipix3RX-based detectors. On a well-calibrated spectral CT scanner, we measured an integral count error of 0.5%, intrascan count variation of 0.1%, and an interscan count variation of less than 1%. The angular offset of the beam center ranged from 0.8° to 1.6° for the studied spectral CT scanners. We also demonstrate the capability of this method to identify poor performance of the system through analyzing the deviation of the experimental beam profile from the model. This technique can, therefore, aid in monitoring the system performance to obtain a robust spectral CT; providing the reliable quantitative images. Furthermore, the accurate offset parameters of a spectral scanner provided by this method allow us to incorporate a more realistic form of the photon distribution in the polychromatic-based image reconstruction models. Both improvements of the reliability of the system and accuracy of the volume reconstruction result in a better discrimination and quantification of the imaged materials.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5849855PMC
http://dx.doi.org/10.1002/acm2.12260DOI Listing

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