Application of non-negative matrix factorization to multispectral FLIM data analysis.
Application of non-negative matrix factorization to multispectral FLIM data analysis.
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DOI：
10.1364/boe.3.002244
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发表时间：
2012-09-01
影响因子：
3.4
通讯作者：
Jo JA
中科院分区：
文献类型：
--
作者：
Pande P;Applegate BE;Jo JA
现有的方法解释荧光寿命成像显微镜（FLIM）图像的基础上比较的强度和寿命值在每个像素与已知的荧光团。这种方法在许多实际应用中变得笨拙和主观，其中存在对本体荧光信号有贡献的几种荧光物质，并且在多光谱FLIM的情况下甚至更是如此。非负矩阵分解（NMF）是一种多元数据分析技术，旨在从纯组分的加性混合物中提取纯组分的非负特征及其非负丰度。在本文中，我们提出了应用NMF多光谱时域FLIM数据，以获得一组新的FLIM功能（相对丰度的组成荧光团）。这些特征比标准荧光强度和寿命值更直观，更容易解释。与几种FLIM数据分析方法不同，所提出的方法不受组成荧光物质的数量或其可能复杂的衰变动力学的限制。此外，FLIM特征的新集合可以通过处理原始多光谱FLIM强度数据来获得，从而使得时间去卷积不必要并且导致更少的计算时间和放松的SNR要求。模拟和实验的多光谱时域FLIM数据的NMF方法的性能进行了验证。NMF特征也与标准强度和寿命特征进行了比较，就其区分不同类型动脉粥样硬化斑块的能力而言。
Existing methods of interpreting fluorescence lifetime imaging microscopy (FLIM) images are based on comparing the intensity and lifetime values at each pixel with those of known fluorophores. This method becomes unwieldy and subjective in many practical applications where there are several fluorescing species contributing to the bulk fluorescence signal, and even more so in the case of multispectral FLIM. Non-negative matrix factorization (NMF) is a multivariate data analysis technique aimed at extracting non-negative signatures of pure components and their non-negative abundances from an additive mixture of those components. In this paper, we present the application of NMF to multispectral time-domain FLIM data to obtain a new set of FLIM features (relative abundance of constituent fluorophores). These features are more intuitive and easier to interpret than the standard fluorescence intensity and lifetime values. The proposed approach, unlike several FLIM data analysis methods, is not limited by the number of constituent fluorescing species or their possibly complex decay dynamics. Moreover, the new set of FLIM features can be obtained by processing raw multispectral FLIM intensity data, thereby rendering time deconvolution unnecessary and resulting in lesser computational time and relaxed SNR requirements. The performance of the NMF method was validated on simulated and experimental multispectral time-domain FLIM data. The NMF features were also compared against the standard intensity and lifetime features, in terms of their ability to discriminate between different types of atherosclerotic plaques.