Multispectral imaging (MSI) is increasingly finding application in the study and characterization of biological specimens. However, the methods typically used come with challenges on both the acquisition and the analysis front. MSI can be slow and photon-inefficient, leading to long imaging times and possible phototoxicity and photobleaching. The resulting datasets can be large and complex, prompting the development of a number of mathematical approaches for segmentation and signal unmixing. We show that under certain circumstances, just three spectral channels provided by standard color cameras, coupled with multispectral analysis tools, including a more recent spectral phasor approach, can efficiently provide useful insights. These findings are supported with a mathematical model relating spectral bandwidth and spectral channel number to achievable spectral accuracy. The utility of 3-band RGB and MSI analysis tools are demonstrated on images acquired using brightfield and fluorescence techniques, as well as a novel microscopy approach employing UV-surface excitation. Supervised linear unmixing, automated non-negative matrix factorization and phasor analysis tools all provide useful results, with phasors generating particularly helpful spectral display plots for sample exploration.

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多光谱分析工具可以增加 RGB 彩色图像在组织学中的效用

多光谱成像 (MSI) 越来越多地应用于生物标本的研究和表征。然而，通常使用的方法在采集和分析方面都面临着挑战。MSI 可能很慢且光子效率低下，导致成像时间长，并可能产生光毒性和光漂白。生成的数据集可能庞大而复杂，促使开发了许多用于分割和信号分解的数学方法。我们表明，在某些情况下，标准彩色相机仅提供三个光谱通道，再加上多光谱分析工具，包括最近的光谱相量方法，就可以有效地提供有用的见解。这些发现得到了将光谱带宽和光谱通道数与可实现的光谱精度相关联的数学模型的支持。3 波段 RGB 和 MSI 分析工具的实用性在使用明场和荧光技术以及采用 UV 表面激发的新型显微镜方法获取的图像上进行了演示。监督线性分解、自动非负矩阵分解和相量分析工具都提供了有用的结果，相量生成特别有用的光谱显示图，用于样品探索。