National Institutes of Health, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Section on Analytical and Functional Biophotonics (PPITS/SAFB), Bethesda, Maryland 20892, USA.
J Biomed Opt. 2010 Jul-Aug;15(4):046007. doi: 10.1117/1.3463010.
Multispectral images of skin contain information on the spatial distribution of biological chromophores, such as blood and melanin. From this, parameters such as blood volume and blood oxygenation can be retrieved using reconstruction algorithms. Most such approaches use some form of pixelwise or volumetric reconstruction code. We explore the use of principal component analysis (PCA) of multispectral images to access blood volume and blood oxygenation in near real time. We present data from healthy volunteers under arterial occlusion of the forearm, experiencing ischemia and reactive hyperemia. Using a two-layered analytical skin model, we show reconstruction results of blood volume and oxygenation and compare it to the results obtained from our new spectral analysis based on PCA. We demonstrate that PCA applied to multispectral images gives near equivalent results for skin chromophore mapping and quantification with the advantage of being three orders of magnitude faster than the reconstruction algorithm.
皮肤的多光谱图像包含有关生物色素（如血液和黑色素）的空间分布的信息。通过这些信息，可以使用重建算法来获取诸如血液量和血液氧合等参数。大多数此类方法都使用某种形式的逐像素或体积重建代码。我们探索使用主成分分析（PCA）对多光谱图像进行分析，以近乎实时地获取血液量和血液氧合。我们展示了健康志愿者在前臂动脉阻塞下的实验数据，该志愿者经历了缺血和反应性充血。我们使用两层分析皮肤模型，展示了血液量和氧合的重建结果，并将其与我们基于 PCA 的新光谱分析的结果进行了比较。我们证明，应用于多光谱图像的 PCA 可以提供近乎等效的皮肤色素映射和量化结果，并且其优势在于比重建算法快三个数量级。
