Abstract
Fluorescence lifetime imaging microscopy (FLIM) can be used to probe concentration profiles of key marco-molecules within sub-cellular environments. However, current analyses for FLIM require a large number of photons per pixel to provide such a quantitative picture of life. In order to acquire such large number of photons, we must either increase data acquisition time, which limits temporal resolution, or increase laser intensity, which causes greater photo damage to the sample, or both. Here, we propose to analyze FLIM data by leveraging tools from the Bayesian paradigm.
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