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Monte Carlo simulation of a mammographic test phantom

Hunt, R. A. ; Dance, D. R. ; Pachoud, M. ; Alm Carlsson, G. ; Sandborg, M. ; Ullman, G. ; Verdun, F. R.

In: Radiation Protection Dosimetry, 2005, vol. 114, no. 1-3, p. 432-435

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    Titel
    • Monte Carlo simulation of a mammographic test phantom
    Autor
    • Hunt, R. A.. Department of Physics, The Royal Marsden Hospital NHS Foundation Trust, London SW3 6JJ, UK
    • Dance, D. R.. Department of Physics, The Royal Marsden Hospital NHS Foundation Trust, London SW3 6JJ, UK
    • Pachoud, M.. University Institute for Applied Radiophysics, Grand-Pré 1 CH-1007 Lausanne, Switzerland
    • Alm Carlsson, G.. Department of Radiation Physics, IMV, Faculty of Health Sciences, Linköping University, SE-58185 Linköping, Sweden
    • Sandborg, M.. Department of Radiation Physics, IMV, Faculty of Health Sciences, Linköping University, SE-58185 Linköping, Sweden
    • Ullman, G.. Department of Radiation Physics, IMV, Faculty of Health Sciences, Linköping University, SE-58185 Linköping, Sweden
    • Verdun, F. R.. University Institute for Applied Radiophysics, Grand-Pré 1 CH-1007 Lausanne, Switzerland
    Dokumententyp
    • Postprint
    Sprache
    • Englisch
    Veröffentlicht in
    • Radiation Protection Dosimetry, 2005, vol. 114, no. 1-3, p. 432-435. Oxford University Press
    Andere elektronische Ausgabe
    Klassifikation
    • Gesundheit
    OAI-PMH-ID
    • oai:doc.rero.ch:296805
    Summary
    A test phantom, including a wide range of mammographic tissue equivalent materials and test details, was imaged on a digital mammographic system. In order to quantify the effect of scatter on the contrast obtained for the test details, calculations of the scatter-to-primary ratio (S/P) have been made using a Monte Carlo simulation of the digital mammographic imaging chain, grid and test phantom. The results show that the S/P values corresponding to the imaging conditions used were in the range 0.084-0.126. Calculated and measured pixel values in different regions of the image were compared as a validation of the model and showed excellent agreement. The results indicate the potential of Monte Carlo methods in the image quality-patient dose process optimisation, especially in the assessment of imaging conditions not available on standard mammographic units