Zeng Gengsheng L, Wang Wenli
Department of Engineering, Weber State University, Ogden, UT 84408 USA and also with the Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT 84108 USA (
Toshiba Medical Research Institute USA Inc., Vernon Hills, IL 60061 USA and also with Columbia University Medical Center, New York, NY 10032 USA.
IEEE Trans Radiat Plasma Med Sci. 2017 Jan;1(1):68-75. doi: 10.1109/TNS.2016.2630685. Epub 2016 Nov 18.
This paper uses a computer simulation to investigate whether a more accurate noise model always results in less noisy images in CT iterative reconstruction. We start with a hypothetic non-realistic noise model for the CT measurements, by assuming that the attenuation coefficient is energy independent and there is no scattering. A variance formula for this model is derived and presented. Based on this model, computer simulations are conducted with 12 different ad hoc noise weighting methods, and their results are compared. The simple Poisson noise model performs better than other more accurate models, when the projection data are generated with the hypothetical noise model. A more accurate noise model does not necessarily produce a less-noisy image. In this counter example, modeling the system's electronic noise during reconstruction does not help reducing the image noise. A simpler noise model sometimes can outperform the complicated and more accurate noise model.
本文使用计算机模拟来研究在CT迭代重建中，更精确的噪声模型是否总能产生噪声更少的图像。我们从一个假设的、不切实际的CT测量噪声模型开始，假设衰减系数与能量无关且不存在散射。推导并给出了该模型的方差公式。基于此模型，采用12种不同的临时噪声加权方法进行计算机模拟，并比较其结果。当使用假设噪声模型生成投影数据时，简单的泊松噪声模型比其他更精确的模型表现更好。更精确的噪声模型不一定能产生噪声更少的图像。在这个反例中，在重建过程中对系统的电子噪声进行建模无助于降低图像噪声。一个更简单的噪声模型有时可能比复杂且更精确的噪声模型表现更好。
