Transforming multispectral images to enhanced resolution images enabled by machine learning

A system comprising:

• a non-transitory computer-readable medium;
• and
• one or more processors configured to execute processor-executable instructions stored in the non-transitory computer-readable medium to:
• receive an input image of a first biological sample, wherein the input image has a first spatial resolution and a plurality of spectral images, and wherein each spectral image of the plurality of spectral images includes data from a different wavelength band at a different spectral channel;
• apply a trained artificial neural network to the input image, the trained artificial neural network trained using an image training data set including a plurality of image pairs, wherein each image pair of the plurality of image pairs includes a first image of a biological sample acquired when the biological sample is unstained, wherein the first image includes a first plurality of spectral images of the biological sample, and wherein each spectral image of the first plurality of spectral images includes data from a different wavelength band;
• and a second image of the biological sample acquired when the biological sample is stained;
• generate an output image at a second spatial resolution, and wherein the output image includes a fewer number of spectral channels than the plurality of spectral images included in the input image;
• and
• output the output image.

A non-transitory computer-readable medium comprising processor-executable instructions configured to cause one or more processors to:

• receive an input image of a first biological sample, wherein the input image has a first spatial resolution and a plurality of spectral images, and wherein each spectral image of the plurality of spectral images includes data from a different wavelength band at a different spectral channel;
• apply a trained artificial neural network to the input image, the trained artificial neural network trained using an image training data set including a plurality of image pairs, wherein each image pair of the plurality of image pairs includes a first image of a biological sample acquired when the biological sample is unstained, wherein the first image includes a first plurality of spectral images of the biological sample, and wherein each spectral image of the first plurality of spectral images includes data from a different wavelength band;
• and a second image of the biological sample acquired when the biological sample is stained;
• generate an output image at a second spatial resolution, and wherein the output image includes a fewer number of spectral channels than the plurality of spectral images included in the input image;
• and
• output the output image.