蒙特卡罗方法
散射
光学
衰减
物理
计算物理学
非相干散射
探测器
光子
能量(信号处理)
航程(航空)
辐射
断层摄影术
信号(编程语言)
计算机科学
材料科学
复合材料
统计
量子力学
程序设计语言
数学
作者
Matteo Busi,Ulrik L. Olsen,Erik Knudsen,Jeppe Revall Frisvad,Jan Kehres,Erik Schou Dreier,Mohamad Khalil,Kristoffer Haldrup
标识
DOI:10.1117/1.oe.57.3.037105
摘要
Spectral computed tomography is an emerging imaging method that involves using recently developed energy discriminating photon-counting detectors (PCDs). This technique enables measurements at isolated high-energy ranges, in which the dominating undergoing interaction between the x-ray and the sample is the incoherent scattering. The scattered radiation causes a loss of contrast in the results, and its correction has proven to be a complex problem, due to its dependence on energy, material composition, and geometry. Monte Carlo simulations can utilize a physical model to estimate the scattering contribution to the signal, at the cost of high computational time. We present a fast Monte Carlo simulation tool, based on McXtrace, to predict the energy resolved radiation being scattered and absorbed by objects of complex shapes. We validate the tool through measurements using a CdTe single PCD (Multix ME-100) and use it for scattering correction in a simulation of a spectral CT. We found the correction to account for up to 7% relative amplification in the reconstructed linear attenuation. It is a useful tool for x-ray CT to obtain a more accurate material discrimination, especially in the high-energy range, where the incoherent scattering interactions become prevailing (>50 keV).
科研通智能强力驱动
Strongly Powered by AbleSci AI