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Simultaneous decomposition of multiple hyperspectral data sets: signal recovery of unknown fluorophores in the retinal pigment epithelium

机译:同时分解多个高光谱数据集:视网膜色素上皮细胞中未知荧光团的信号恢复

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Upon excitation with different wavelengths of light, biological tissues emit distinct but related autofluorescence signals. We used non-negative matrix factorization (NMF) to simultaneously decompose co-registered hyperspectral emission data from human retinal pigment epithelium/Bruch’s membrane specimens illuminated with 436 and 480 nm light. NMF analysis was initialized with Gaussian mixture model fits and constrained to provide identical abundance images for the two excitation wavelengths. Spectra recovered this way were smoother than those obtained separately; fluorophore abundances more clearly localized within tissue compartments. These studies provide evidence that leveraging multiple co-registered hyperspectral emission data sets is preferential for identifying biologically relevant fluorophore information.
机译:在用不同波长的光激发后,生物组织发出不同但相关的自发荧光信号。我们使用非负矩阵分解(NMF),同时分解了人类视网膜色素上皮/布鲁赫膜标本在436和480 nm光照下的共同注册的高光谱发射数据。 NMF分析使用高斯混合模型拟合进行初始化,并被约束为两个激发波长提供相同的丰度图像。用这种方法回收的光谱比单独获得的光谱要平滑。荧光团的丰度更清晰地位于组织隔室内。这些研究提供了证明,利用多个共同注册的高光谱发射数据集对于识别生物学上相关的荧光团信息是优先的。

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