Numerical Spectral Demultiplexing Microscopy of Measurements from an Anatomical Specimen

Multispectral microscopy is a method of capturing spectral bands using a microscope, and is used to observe specimens on a micron or nano scale. However, these systems are limited because they cannot capture transient phenomena since they cannot capture simultaneous spectral information. We propose a new method called numerical spectral demultiplexing microscopy (NSDM) which utilizes a Raspberry Pi camera to capture RGB measurements and then infer narrow-band multispectral spectra. This is accomplished by training a non-linear regression random forest model based on the spectral sensitivity of the camera which allows for a low-cost, portable, and simultaneous capture multispectral microscopy system. We use the NSDM system as a bright-field multispectral microscope and a dark-field fluorescence multispectral microscope on an anatomical specimen and show that additional information can be gathered by combining a bright-field and dark-field fluorescence microscope.