Unstained multimodal microscopy is capable of non-invasively obtaining chemically specific information with sub-micron spatial resolution; however, spectral overlap makes quantitative analysis difficult. Here, multimodal images that include second-harmonic generation, third-harmonic generation, and two- and three-photon excited fluorescence signals from unstained retinas are analyzed. The composition from each layer of the retina is determined using a novel variation of phasor analysis that is not limited to three components. The super-phasor unmixing (SPU) method is compared with fully constrained linear spectral unmixing. The seven spectroscopic signals in the spectral range 300–690 nm enable the quantitative unmixing of sub-micron pixel spectra even in the presence of noise. The performance of SPU was found to be significantly superior to linear unmixing especially in regions of high spectral overlap. The analysis being presented represents an important step in addressing chemical complexity in congested spaces with applicability to biomedical imaging and unmixing of hyperspectral images.

未染色的多峰显微镜能够无创地获得亚微米空间分辨率的化学特异信息；但是，光谱重叠使定量分析变得困难。在这里，分析了包括二次谐波产生，三次谐波产生以及来自未染色视网膜的双光子和三光子激发荧光信号在内的多峰图像。使用不限于三个分量的新型相量分析来确定来自视网膜每一层的成分。将超相量解混（SPU）方法与完全约束的线性光谱解混进行了比较。即使在存在噪声的情况下，在300-690 nm光谱范围内的七个光谱信号也可以定量分解亚微米像素光谱。发现SPU的性能明显优于线性解混，特别是在高光谱重叠区域。提出的分析代表了解决拥挤空间中化学物质复杂性的重要步骤，适用于生物医学成像和高光谱图像的分解。