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Rectified subspace analysis of dynamic positron emission tomography

机译:动态正电子发射断层扫描的整流子空间分析

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Subspace analysis is a popular method for multivariate data analysis and is closely related to factor analysis and principal component analysis (PCA). In the context of image processing (especially positron emission tomography), all data points are nonnegative and it is expected that both basis images and factors are nonnegative in order to obtain reasonable results. Recently the nonnegative matrix factorization (NMF) was introduced [6]. It was demonstrated that the NMF gave parts-based representation [6] and was useful in dynamic PET image analysis [9]. In this paper we present a sequential EM algorithm for rectified subspace analysis (subspace in nonnegativity constraint) and apply it to dynamic PET image analysis. Experimental results show that our proposed method is useful in dynamic PET image analysis.
机译:子空间分析是多元数据分析的流行方法,与因子分析和主成分分析(PCA)密切相关。在图像处理(尤其是正电子发射断层扫描)的背景下,所有数据点都是非负的,并且预期基础图像和因素都是非负的,以获得合理的结果。最近,引入了非负基质分解(NMF)[6]。结果证明NMF给出了基于部件的代表[6],可用于动态PET图像分析[9]。本文介绍了一种序列EM算法,用于整流子空间分析(非室内限制中的子空间),并将其应用于动态PET图像分析。实验结果表明,我们所提出的方法可用于动态宠物图像分析。

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