Abstract: A fluorescence lifetime imaging microscopy system comprises a microscope comprising an excitation source configured to direct an excitation energy to an imaging target, and a detector configured to measure emissions of energy from the imaging target, and a non-transitory computer-readable medium with instructions stored thereon, which perform steps comprising collecting a quantity of measured emissions of energy from the imaging target as measured data, providing a trained neural network configured to calculate fluorescent decay parameters from the quantity of measured emissions of energy, providing the data to the trained neural network, and calculating at least one fluorescence lifetime parameter with the neural network from the measured data, wherein the measured data comprises an input fluorescence decay histogram, and wherein the neural network was trained by a generative adversarial network. A method of training a neural network and a method of acquiring an image are also described.