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A hybrid approach to Simulate X-ray imaging techniques, combining Monte Carlo and deterministic algorithms

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3 Author(s)
Freud, N. ; Lab. of Nondestructive Testing using Ionizing Radiat.s, INSA-Lyon Sci. & Tech. Univ., Villeurbanne, France ; Letang, J.-M. ; Babot, D.

In this paper, we propose a hybrid approach to simulate multiple scattering of photons in objects under X-ray inspection, without recourse to parallel computing and without any approximation sacrificing accuracy. Photon scattering is considered from two points of view: it contributes to X-ray imaging and to the dose absorbed by the patient. The proposed hybrid approach consists of a Monte Carlo stage followed by a deterministic phase, thus taking advantage of the complementarity between these two methods. In the first stage, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Then this set of scattering events is used to compute the energy imparted to the detector, with a deterministic algorithm based on a "forced detection" scheme. Regarding dose evaluation, we propose to assess separately the energy deposited by direct radiation (using a deterministic algorithm) and by scattered radiation (using our hybrid approach). The results obtained in a test case are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the required detector resolution and statistics). It is possible to simulate radiographic images virtually free from photon noise. In the case of dose evaluation, the hybrid approach appears particularly suitable to calculate the dose absorbed by regions of interest (rather than the entire irradiated organ) with computation time and statistical fluctuations considerably reduced in comparison with conventional Monte Carlo simulation.

Published in:

Nuclear Science, IEEE Transactions on  (Volume:52 ,  Issue: 5 )

Date of Publication:

Oct. 2005

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