کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8168793 | 1526296 | 2016 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A hybrid Monte Carlo model for the energy response functions of X-ray photon counting detectors
ترجمه فارسی عنوان
یک مدل هیبرید مونت کارلو برای توابع پاسخ انرژی از آشکارسازهای شمارش فوتون اشعه ایکس
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کلمات کلیدی
فوتون شمارش آشکارساز، مدل سازی، توموگرافی کامپیوتری، تصویربرداری اشعه ایکس،
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
ابزار دقیق
چکیده انگلیسی
In photon counting computed tomography (CT), it is vital to know the energy response functions of the detector for noise estimation and system optimization. Empirical methods lack flexibility and Monte Carlo simulations require too much knowledge of the detector. In this paper, we proposed a hybrid Monte Carlo model for the energy response functions of photon counting detectors in X-ray medical applications. GEANT4 was used to model the energy deposition of X-rays in the detector. Then numerical models were used to describe the process of charge sharing, anti-charge sharing and spectral broadening, which were too complicated to be included in the Monte Carlo model. Several free parameters were introduced in the numerical models, and they could be calibrated from experimental measurements such as X-ray fluorescence from metal elements. The method was used to model the energy response function of an XCounter Flite X1 photon counting detector. The parameters of the model were calibrated with fluorescence measurements. The model was further tested against measured spectrums of a VJ X-ray source to validate its feasibility and accuracy.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment - Volume 830, 11 September 2016, Pages 397-406
Journal: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment - Volume 830, 11 September 2016, Pages 397-406
نویسندگان
Dufan Wu, Xiaofei Xu, Li Zhang, Sen Wang,