Mimicking multimodal contrast with vertex component analysis of hyperspectral CARS images

Abstract

We show the applicability of vertex component analysis (VCA) of hyperspectral CARS images in generating a similar contrast profile to that obtained in "multimodal imaging" that uses signals from three separate nonlinear optical techniques. Using an atherosclerotic rabbit aorta test image, we show that the VCA algorithm provides pseudocolor contrast that is comparable to multimodal imaging, thus suggesting that under certain conditions much of the information gleaned from a multimodal nonlinear optical approach can be sufficiently extracted from the CARS hyperspectral stack itself. This is useful for unsupervised contrast generation on hyperspectral CARS implementations such as multiplex CARS that may not have multimodal capabilities. The utility of VCA as a quantitative analysis tool in CARS is also addressed.