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A spectroscopic approach based on Non-negative Matrix Factorization method for multispectral fluorescence images unmixing

机译:基于非负矩阵分解的光谱方法用于多光谱荧光图像分解

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Immunofluorescence is the visualization of organs using antibodies as fluorescent probes. It allows to detect and to localize one or more fluorescent labeled structure using specific antibodies. A major problem in this regard is the autofluorescence present in some biological samples. The spatial localization analysis of interest structures is often perturbed by a significant overlap between the marker fluorescence and the biological tissues autofluorescence. This overlap leads to the formation of a complex multicolored image. Indeed, the surface covered by one pixel of such image may contain more than one fluorescent sources component. Thus, the spectrum observed in each pixel may be a linear mixture of contributions from several sources. A spectroscopic approach, based on the Non-negative Matrix Factorization (NMF) method, is explored to decompose each mixed pixel spectrum into several pure fluorescent spectra and their relative contributions. This blind source separation method treats specific fluorescence and autofluorescence as different sources to separate. Experimental results on real mixtures confirm the effectiveness of the proposed method.
机译:免疫荧光是使用抗体作为荧光探针的器官的可视化。它允许使用特异性抗体检测并定位一种或多种荧光标记的结构。在这方面的主要问题是某些生物样品中存在的自发荧光。感兴趣结构的空间定位分析通常会受到标记荧光和生物组织自发荧光之间的明显重叠的干扰。这种重叠导致形成复杂的彩色图像。实际上,由此类图像的一个像素覆盖的表面可能包含一个以上的荧光源组件。因此,在每个像素中观察到的光谱可以是来自多个源的贡献的线性混合。探索了一种基于非负矩阵分解(NMF)方法的光谱方法,将每个混合像素光谱分解为几个纯荧光光谱及其相对贡献。这种盲源分离方法将特定的荧光和自发荧光视为要分离的不同光源。真实混合物的实验结果证实了该方法的有效性。

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