Paper
20 April 2005 Coupling an analytical description of anti-scatter grids with simulation software of radiographic systems using Monte Carlo code
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Abstract
The use of focused anti-scatter grids on digital radiographic systems with two-dimensional detectors produces acquisitions with a decreased scatter to primary ratio and thus improved contrast and resolution. Simulation software is of great interest in optimizing grid configuration according to a specific application. Classical simulators are based on complete detailed geometric descriptions of the grid. They are accurate but very time consuming since they use Monte Carlo code to simulate scatter within the high-frequency geometric description of the grid. We propose a new practical method which couples an analytical simulation of the grid interaction with a radiographic system simulation program. First, a two dimensional matrix of probability depending on the grid is created offline, in which the first dimension represents the angle of impact with respect to the normal to the grid lines and the other the energy of the photon. This matrix of probability is then used by the Monte Carlo simulation software in order to provide the final x-rays scatter flux image. To evaluate the gain of CPU time, we define the increasing factor as the increase of CPU time of the simulation with as or without the grid. Increasing factors were calculated with the new model and with classical methods representing the grid with a Computed-Aided Designed (CAD) model. With this new method, increasing factors are shortened by three to four orders of magnitude.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jean Rinkel, Joachim Tabary, Francois Esteve, and Jean-Marc Dinten "Coupling an analytical description of anti-scatter grids with simulation software of radiographic systems using Monte Carlo code", Proc. SPIE 5745, Medical Imaging 2005: Physics of Medical Imaging, (20 April 2005); https://doi.org/10.1117/12.593632
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KEYWORDS
Monte Carlo methods

Sensors

Computer aided design

Computer simulations

Solid modeling

3D modeling

Data modeling

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