End-to-end design of multicolor scintillators for enhanced energy resolution in X-ray imaging

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Publicat a:arXiv.org (Oct 11, 2024), p. n/a
Autor principal: Seokhwan Min
Altres autors: Choi, Seou, Pajovic, Simo, Vaidya, Sachin, Rivera, Nicholas, Fan, Shanhui, Marin Soljačić, Roques-Carmes, Charles
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Cornell University Library, arXiv.org
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Accés en línia:Citation/Abstract
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022 |a 2331-8422 
035 |a 3116454789 
045 0 |b d20241011 
100 1 |a Seokhwan Min 
245 1 |a End-to-end design of multicolor scintillators for enhanced energy resolution in X-ray imaging 
260 |b Cornell University Library, arXiv.org  |c Oct 11, 2024 
513 |a Working Paper 
520 3 |a Scintillators have been widely used in X-ray imaging due to their ability to convert high-energy radiation into visible light, making them essential for applications such as medical imaging and high-energy physics. Recent advances in the artificial structuring of scintillators offer new opportunities for improving the energy resolution of scintillator-based X-ray detectors. Here, we present a three-bin energy-resolved X-ray imaging framework based on a three-layer multicolor scintillator used in conjunction with a physics-aware image postprocessing algorithm. The multicolor scintillator is able to preserve X-ray energy information through the combination of emission wavelength multiplexing and energy-dependent isolation of X-ray absorption in specific layers. The dominant emission color and the radius of the spot measured by the detector are used to infer the incident X-ray energy based on prior knowledge of the energy-dependent absorption profiles of the scintillator stack. Through ab initio Monte Carlo simulations, we show that our approach can achieve an energy reconstruction accuracy of 49.7%, which is only 2% below the maximum accuracy achievable with realistic scintillators. We apply our framework to medical phantom imaging simulations where we demonstrate that it can effectively differentiate iodine and gadolinium-based contrast agents from bone, muscle, and soft tissue. 
653 |a Gadolinium 
653 |a Energy resolution 
653 |a Iodine 
653 |a X ray imagery 
653 |a Image reconstruction 
653 |a Contrast agents 
653 |a X ray absorption 
653 |a X ray detectors 
653 |a Emission 
653 |a Monte Carlo simulation 
653 |a Medical imaging 
653 |a Multiplexing 
653 |a Scintillation counters 
653 |a Soft tissues 
653 |a Algorithms 
653 |a Energy 
653 |a Computer simulation 
700 1 |a Choi, Seou 
700 1 |a Pajovic, Simo 
700 1 |a Vaidya, Sachin 
700 1 |a Rivera, Nicholas 
700 1 |a Fan, Shanhui 
700 1 |a Marin Soljačić 
700 1 |a Roques-Carmes, Charles 
773 0 |t arXiv.org  |g (Oct 11, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3116454789/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2410.08543