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Simulation of scanner- and patient-specific low-dose CT imaging from existing CT images.
Naziroglu, Robiël E; van Ravesteijn, Vincent F; van Vliet, Lucas J; Streekstra, Geert J; Vos, Frans M.
Afiliação
  • Naziroglu RE; Quantitative Imaging Group, Delft University of Technology, NL-2628 CJ Delft, The Netherlands. Electronic address: R.E.Naziroglu@tudelft.nl.
  • van Ravesteijn VF; Quantitative Imaging Group, Delft University of Technology, NL-2628 CJ Delft, The Netherlands.
  • van Vliet LJ; Quantitative Imaging Group, Delft University of Technology, NL-2628 CJ Delft, The Netherlands. Electronic address: L.J.vanVliet@tudelft.nl.
  • Streekstra GJ; Department of Biomedical Engineering and Physics, Academic Medical Center, NL-1105 AZ Amsterdam, The Netherlands; Department of Radiology, Academic Medical Center, NL-1100 DD Amsterdam, The Netherlands. Electronic address: g.j.streekstra@amc.uva.nl.
  • Vos FM; Quantitative Imaging Group, Delft University of Technology, NL-2628 CJ Delft, The Netherlands; Department of Radiology, Academic Medical Center, NL-1100 DD Amsterdam, The Netherlands. Electronic address: F.M.Vos@tudelft.nl.
Phys Med ; 36: 12-23, 2017 Apr.
Article em En | MEDLINE | ID: mdl-28410681
PURPOSE: Simulating low-dose Computed Tomography (CT) facilitates in-silico studies into the required dose for a diagnostic task. Conventionally, low-dose CT images are created by adding noise to the projection data. However, in practice the raw data is often simply not available. This paper presents a new method for simulating patient-specific, low-dose CT images without the need of the original projection data. METHODS: The low-dose CT simulation method included the following: (1) computation of a virtual sinogram from a high dose CT image through a radon transform; (2) simulation of a 'reduced'-dose sinogram with appropriate amounts of noise; (3) subtraction of the high-dose virtual sinogram from the reduced-dose sinogram; (4) reconstruction of a noise volume via filtered back-projection; (5) addition of the noise image to the original high-dose image. The required scanner-specific parameters, such as the apodization window, bowtie filter, the X-ray tube output parameter (reflecting the photon flux) and the detector read-out noise, were retrieved from calibration images of a water cylinder. The low-dose simulation method was evaluated by comparing the noise characteristics in simulated images with experimentally acquired data. RESULTS: The models used to recover the scanner-specific parameters fitted accurately to the calibration data, and the values of the parameters were comparable to values reported in literature. Finally, the simulated low-dose images accurately reproduced the noise characteristics in experimentally acquired low-dose-volumes. CONCLUSION: The developed methods truthfully simulate low-dose CT imaging for a specific scanner and reconstruction using filtered backprojection. The scanner-specific parameters can be estimated from calibration data.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doses de Radiação / Simulação por Computador / Tomografia Computadorizada por Raios X Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doses de Radiação / Simulação por Computador / Tomografia Computadorizada por Raios X Idioma: En Ano de publicação: 2017 Tipo de documento: Article