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.

FRAP, FLIM, and FRET: Detection and analysis of cellular dynamics on a molecular scale using fluorescence microscopy

“…For time‐domain FLIM, novel total variation‐based denoising methods have been applied to both time‐gated and multi‐photon TCSPC FLIM. These approaches have been compared with wavelet‐based denoising methods, and have shown superior results (Chang and Mycek, ); indeed, a multi‐fold precision improvement is achieved without compromising the accuracy of measurements, and even greater improvement of FLIM can be achieved when used in combination with optimal (virtual) gating (Chang and Mycek, ,, ,).…”

Fluorescence in depth: integration of spectroscopy and imaging with Raman, IR, and CD for advanced research

“…TRFS provides precise measurements of fluorescence lifetimes, enabling analysis of molecular interactions and dynamic processes with high temporal resolution [4]. FLIM, an imaging variant of TRFS, extends these capabilities to provide spatially resolved fluorescence lifetime information, enabling the study of cellular processes and protein interactions [5]. Raman Spectroscopy harnesses the inelastic scattering of photons to provide molecular fingerprinting.…”

Tensor regularized total variation for denoising of third harmonic generation images of brain tumors

“…The combination of ADF and the total variation (TV) model [27][28][29] provides an approach to overcome the drawbacks of the ADF models. TV regularization is another standard denoising method that has been studied mathematically for over decades [30][31][32][33][34][35].…”