Department of Radiology, Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, UT 84112, USA.
IEEE Trans Med Imaging. 2010 May;29(5):1097-113. doi: 10.1109/TMI.2009.2034961. Epub 2010 Mar 15.
We introduce a new estimator for noise variance in tomographic images reconstructed using algorithms of the filtered backprojection type. The new estimator operates on data acquired from repeated scans of the object under examination, is unbiased, and is shown to have significantly lower variance than the conventional unbiased estimator for many scenarios of practical interest. We provide an extensive theoretical analysis of this estimator, highlighting the circumstances under which it is most effective. This analysis includes both general and specific data-correlation patterns. Moreover, we have applied our estimator to real X-ray computed tomography data and present preliminary results that support the theory and provide experimental evidence of the new estimator's efficacy.
我们引入了一种新的估计量,用于估计使用滤波反投影类型算法重建的层析图像中的噪声方差。新的估计量基于对被检物体的重复扫描获取的数据进行操作,是无偏的,并且在许多实际感兴趣的情况下,其方差明显低于传统的无偏估计量。我们对该估计量进行了广泛的理论分析,突出了它最有效的情况。该分析包括一般和特定的数据相关模式。此外,我们已经将我们的估计器应用于真实的 X 射线计算机层析成像数据,并提出了初步结果,这些结果支持了该理论,并提供了新估计器有效性的实验证据。