Development of a scanner-specific simulation framework for photon-counting computed tomography.

Journal Article (Journal Article)

The aim of this study was to develop and validate a simulation platform that generates photon-counting CT images of voxelized phantoms with detailed modeling of manufacturer-specific components including the geometry and physics of the x-ray source, source filtrations, anti-scatter grids, and photon-counting detectors. The simulator generates projection images accounting for both primary and scattered photons using a computational phantom, scanner configuration, and imaging settings. Beam hardening artifacts are corrected using a spectrum and threshold dependent water correction algorithm. Physical and computational versions of a clinical phantom (ACR) were used for validation purposes. The physical phantom was imaged using a research prototype photon-counting CT (Siemens Healthcare) with standard (macro) mode, at four dose levels and with two energy thresholds. The computational phantom was imaged with the developed simulator with the same parameters and settings used in the actual acquisition. Images from both the real and simulated acquisitions were reconstructed using a reconstruction software (FreeCT). Primary image quality metrics such as noise magnitude, noise ratio, noise correlation coefficients, noise power spectrum, CT number, in-plane modulation transfer function, and slice sensitivity profiles were extracted from both real and simulated data and compared. The simulator was further evaluated for imaging contrast materials (bismuth, iodine, and gadolinium) at three concentration levels and six energy thresholds. Qualitatively, the simulated images showed similar appearance to the real ones. Quantitatively, the average relative error in image quality measurements were all less than 4% across all the measurements. The developed simulator will enable systematic optimization and evaluation of the emerging photon-counting computed tomography technology.

Full Text

Duke Authors

Cited Authors

  • Abadi, E; Harrawood, B; Rajagopal, JR; Sharma, S; Kapadia, A; Segars, WP; Stierstorfer, K; Sedlmair, M; Jones, E; Samei, E

Published Date

  • August 2019

Published In

Volume / Issue

  • 5 / 5

PubMed ID

  • 33304618

Pubmed Central ID

  • PMC7725233

Electronic International Standard Serial Number (EISSN)

  • 2057-1976

Digital Object Identifier (DOI)

  • 10.1088/2057-1976/ab37e9


  • eng

Conference Location

  • England