Attenuation Correction of Pet Image Reconstructed Based on Direct Filtering of the Raw Data Acquired Using Mcnpx Code

This paper presents the Monte Carlo simulation of the Positron Emission Tomography (PET) scanning technique using MCNPX code. The raw data generated by general MCNPX code contain a lot of unnecessary information for the image reconstruction process. This requires a large memory to store all this information. In order to reduce the needed memory, we introduce some modifications on the MCNPX code source in order to be able to write directly the important data representing the coincidence events detected by the detector pairs along the lines of response (LORs). These data are acquired as a result of launching two simulations on a uniform cylindrical positron emitter source in water-filled environment. Thereafter, from the object’s geometry, knowledge of the materials in this object and the acquired simulation data, the attenuation correction map has been calculated and applied to the acquired data during PET image reconstruction process.