Abstract

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.

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