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4 March 2019 Analytical model for designing a high-energy-efficiency granular double-layer X-ray scintillator with a diffuse reflection layer (Conference Presentation)
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Abstract
Indirect digital X-ray scintillator has been widely used in various medical radiographic and diagnostic applications. To get a clear detection image for precise diagnosis with minimizing the X-ray radiation exposure to the patients, high performance X-ray scintillator is required. The double layer scintillator with having diffuse reflection layer is growing interest composed of highly-scattering scintillator particles are on top of the scintillator. However, since few researches has been studied for the scintillator, the analytic model for expecting and analyzing the scintillator performance is required. Here, we propose the analytic model for expecting the energy efficiency of the granular X-ray double layer scintillator, which is well matched with Monte-Carlo simulation in accuracy of 98%. And furthermore, we suggest the design strategy for achieving high energy efficiency with the satisfaction of sufficient spatial resolution and the design parameters, such as particle size and the thickness of the each layer, are determined. Compared with the Monte Carlo calculation time, our analytical calculation took time only half second, which was 40,000 times faster. Our simple, efficient analytic model has an impact that expectation of energy efficiency in X-ray double layer scintillator can be fulfilled easily without losing accuracy. Furthermore, various cases of design parameters can be tested in advance with the model before manufacturing and designing the X-ray scintillator devices.
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© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jookwon Song, Hyeon Bo Shim, and Jae W. Hahn "Analytical model for designing a high-energy-efficiency granular double-layer X-ray scintillator with a diffuse reflection layer (Conference Presentation)", Proc. SPIE 10870, Design and Quality for Biomedical Technologies XII, 108700O (4 March 2019); https://doi.org/10.1117/12.2508247
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