虚拟乳腺模型中非高斯统计特性的评估。
Evaluation of non-Gaussian statistical properties in virtual breast phantoms.
作者信息
Abbey Craig K, Bakic Predrag R, Pokrajac David D, Maidment Andrew D A, Eckstein Miguel P, Boone John M
机构信息
University of California, Santa Barbara, Department of Psychological and Brain Sciences, Santa Barbara, California, United States.
University of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania, United States.
出版信息
J Med Imaging (Bellingham). 2019 Apr;6(2):025502. doi: 10.1117/1.JMI.6.2.025502. Epub 2019 Jun 14.
Images derived from a "virtual phantom" can be useful in characterizing the performance of imaging systems. This has driven the development of virtual breast phantoms implemented in simulation environments. In breast imaging, several such phantoms have been proposed. We analyze the non-Gaussian statistical properties from three classes of virtual breast phantoms and compare them to similar statistics from a database of breast images. These include clustered-blob lumpy backgrounds (CBLBs), truncated binary textures, and the UPenn virtual breast phantoms. We use Laplacian fractional entropy (LFE) as a measure of the non-Gaussian statistical properties of each simulation procedure. Our results show that, despite similar power spectra, the simulation approaches differ considerably in LFE with very low scores for the CBLB to high values for the UPenn phantom at certain frequencies. These results suggest that LFE may have value in developing and tuning virtual phantom simulation procedures.
从“虚拟体模”获得的图像有助于表征成像系统的性能。这推动了在模拟环境中实现的虚拟乳房体模的发展。在乳房成像中，已经提出了几种这样的体模。我们分析了三类虚拟乳房体模的非高斯统计特性，并将它们与来自乳房图像数据库的类似统计数据进行比较。这些包括聚类斑点状块状背景（CBLB）、截断二元纹理和宾夕法尼亚大学虚拟乳房体模。我们使用拉普拉斯分数熵（LFE）作为每个模拟过程非高斯统计特性的度量。我们的结果表明，尽管功率谱相似，但模拟方法在LFE方面有很大差异，在某些频率下，CBLB的分数非常低，而宾夕法尼亚大学体模的分数很高。这些结果表明，LFE在开发和调整虚拟体模模拟程序方面可能具有价值。
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