Invention Reference Number
Research aimed at understanding sub-cellular biological process requires chemical visualization at sub- micron spatial resolutions. This has been the impetus toward the development of mass spectrometry imaging approaches with sub-cellular resolution. However, the combination of spatial and spectral limitations of the existing techniques makes this direct measurement practically infeasible. Here, we have developed a machine-learning-enabled approach to infer intact molecular spectra with down to 100 nm spatial resolution through machine learning.