Smartphone-enabled snapshot multispectral autofluorescence imaging and its application for bacteria assessments in skin and oral cavity

Abstract

We propose a smartphone-enabled system and method to realize multispectral autofluorescence imaging for analyzing bacterial infection within skin and oral cavity. The system consists of an unmodified and intact commercial smartphone and a home-made cell phone case with built-in black light LEDs. We use Wiener estimation method to calibrate the RGB-mode smartphone camera and transform the acquired autofluorescence photographs into pseudo-multispectral data cubes with 15 wavebands ranging from 420 nm to 700 nm. Then, we extract and compare the spectral performance of emissions from bacteria-produced porphyrins and endogenous background tissue. Based on the extracted autofluorescence spectra, we apply weighted subtraction between wavebands of interest to realize bacteria targeting and feature mapping. We conduct analysis of autofluorescence on facial skin and dental plaques to demonstrate the performance of the proposed system and methods. Further, with this strategy, we realize quantitative analysis of the bacterial infection in the combination and oily types of skin. Compared to traditional bacteria assessment strategies, we provide a method with the features of real-time visualization, label-free molecular identification, and feature mapping. Meanwhile, differing from the most conventional multispectral imaging systems, the proposed smartphone-based system works in a snapshot mode, thus improving its immunity to motion artifacts. Considering the popularity of smartphones in today's world, it is expected a relatively easy acceptance of the proposed cost-effective method by the community, making an impact on skin and oral care in general and in rural areas with low resource settings in particular.