The interest in fluorescence lifetime imaging microscopy (FLIM) is increasing, as commercial FLIM modules become
available for confocal and multi-photon microscopy. In biological FLIM applications, low fluorescence signals from
samples can be a challenge, and this causes poor precision in lifetime. In this study, for the first time, we applied
wavelet-based denoising methods in time-domain FLIM, and compared them with our previously developed total
variation (TV) denoising methods. They were first tested using artificial FLIM images. We then applied them to lowlight
live-cell images. The results demonstrated that our TV methods could improve lifetime precision multi-fold in
FLIM images and preserve the overall lifetime and pre-exponential term values when improving local lifetime fitting,
while wavelet-based methods were faster. The results here can enhance the precision of FLIM, especially for low-light
and / or fast video-rate imaging, to improve current and rapidly emerging new applications of FLIM such as live-cell, in
vivo whole-animal, or endoscopic imaging.
We report data collected with a specialized transient digitizer, high repetition rate microchip laser sources, and fiber
optic light delivery and collection for rapid remote sensing in tissue-simulating phantoms. The instrumentation is highly
suitable for eventual translation to a clinical setting owing to the speed of data acquisition and small footprint. Ranges for
data acquisition time and instrument sensitivity were determined by measuring wavelength time matrices (WTMs) from
tissue-simulating phantoms. Accuracy of WTM data was validated by comparison with Monte-Carlo simulations of
fluorescent light propagation in turbid media.
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