journal article·2020-12-31

Development of a Gamma Camera with a Diverging Collimator Using DMLS 3D Printing

Jong-Hun Won, Dong-Hee Han, Seung-Jae Lee, Cheol-Ha Baek

Journal of Magnetics· Volume 25· Issue 4
Publisher page

Abstract

The purpose of this study is to use a Monte Carlo simulation to derive optimal values for collimator design variables and to produce an optimized collimator for a gamma camera using a 3D printing direct metal laser sintering (DMLS) technique. For the optimization studies, GATE (Geant4 application for tomographic emission) simulation was used, and we tested lead, tungsten, and a full absorber. A total of 15 design variables were simulated using hole sizes of 0.5 mm, 0.7 mm, and 1.0 mm and slat heights from 10 mm to 20 mm at intervals of 2.5 mm. The scintillator used GAGG (gadolinium aluminum gallium garnet) and was set to a size of 25.8 × 25.8 mm². The radiation of the source used in the simulation was 37 MBq, and the source was a 140 keV point source. To obtain the diverging collimator optimization design variables, the point source was detected and an image was acquired to analyze the sensitivity and spatial resolution values. As a result, tungsten, which has good hardness, was used. If the source is located in the center of the diverging collimator, the FWHM is limited to 3.0 mm or less. The optimization value is obtained by considering the permeability, sensitivity, and spatial resolution at a height of 15 mm or higher. The results obtained by moving the source were also similar to those obtained when the source was located at the center. Based on the values of the optimized design variables, this study designed and produced a collimator using DMLS, which is a 3D printing technique. We believe this process can be applied in various fields, such as medical and industrial sectors; optimized collimators can be produced for different purposes while maintaining high precision.
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Research context

OpenAlex topics: Advanced X-ray and CT Imaging · Medical Imaging Techniques and Applications · Infrared Target Detection Methodologies

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