Modeling, Simulation and Analysis of a Clinical PET System With GATE Software and Monte Carlo Model

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Description
Positron emission tomography (PET) is a non-invasive molecular imaging technique widely used for the quantification of physiological and biochemical processes in preclinical and clinical research. Due to its fundamental role in the health care system, there is a constant need

Positron emission tomography (PET) is a non-invasive molecular imaging technique widely used for the quantification of physiological and biochemical processes in preclinical and clinical research. Due to its fundamental role in the health care system, there is a constant need for improvement and optimization of its scanner systems and protocols leading to a dedicated active area of research for PET. (Geant4 Application for Tomographic Emission (GATE) is a simulation platform designed to model and analyze a medical device. Monte Carlo simulations are essential tools to assist in optimizing the data acquisition protocols or in evaluating the correction methods for improved image quantification. Using GATE along with Customizable and Advanced Software for Tomographic Reconstruction (CASToR), provides a link to reconstruct the images.

The goal of this thesis is to learn PET systems that involve Monte Carlo methods, GATE software, CASToR software to model, simulate and analyze PET systems using three clinical PET systems as a template. Fluorine-18 radioisotope source is used to perform measurements on the modeled PET systems. Parameters such as scatter-fraction, random-fraction, sensitivity, count rate performance, signal to noise ratio (SNR), and time of flight (ToF) are analyzed to determine the performance of the systems. Also, the simulated data are provided as input to CASToR software and Amide's a Medical Image Data Examiner (AMIDE) tool to obtain the reconstructed images which are used to analyze the reconstruction capability of the simulated models. The Biograph Vision PET model has high sensitivity (11.159 cps/MBq) and SNR (12.556) while the Ultra-High Resolution (UHR) PET model has high resolution of the reconstructed image.
Date Created
2020
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