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Total variation versus wavelet‐based methods for image denoising in fluorescence lifetime imaging microscopy
Author(s) -
Chang ChingWei,
Mycek MaryAnn
Publication year - 2012
Publication title -
journal of biophotonics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 66
eISSN - 1864-0648
pISSN - 1864-063X
DOI - 10.1002/jbio.201100137
Subject(s) - noise reduction , wavelet , microscopy , artificial intelligence , fluorescence lifetime imaging microscopy , noise (video) , computer science , computer vision , materials science , fluorescence , optics , image (mathematics) , physics
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. (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)