title: Total variation versus wavelet-based methods for image denoising in fluorescence lifetime imaging microscopy.
abstract: We report the first application of wavelet-based denoising (noise removal) methods to time-domain box-car fluorescence lifetime imaging microscopy (FLIM) images and compare the results to novel total variation (TV) denoising methods. Methods were tested first on artificial images and then applied to low-light live-cell images. Relative to undenoised images, TV methods could improve lifetime precision up to 10-fold in artificial images, while preserving the overall accuracy of lifetime and amplitude values of a single-exponential decay model and improving local lifetime fitting in live-cell images. Wavelet-based methods were at least 4-fold faster than TV methods, but could introduce significant inaccuracies in recovered lifetime values. The denoising methods discussed can potentially enhance a variety of FLIM applications, including live-cell, in vivo animal, or endoscopic imaging studies, especially under challenging imaging conditions such as low-light or fast video-rate imaging.
authors.affiliation: Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109-2099, USA.
authors.forename: Ching-Wei
authors.initials: CW
authors.lastname: Chang
authors.forename: Mary-Ann
authors.initials: MA
authors.lastname: Mycek
mesh_terms: D002470:Cell Survival; D045325:HCT116 Cells; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008856:Microscopy, Fluorescence / Q000379:methods*; D016012:Poisson Distribution; D013997:Time Factors