Abstract
Fluorescence microscopy images are inevitably contaminated by background intensity contributions. Fluorescence from out-of-focus planes and scattered light are important sources of slowly varying, low spatial frequency background, whereas background varying from pixel to pixel (high frequency noise) is introduced by the detection system. Here we present a powerful, easy-to-use software, wavelet-based background and noise subtraction (WBNS), which effectively removes both of these components. To assess its performance, we apply WBNS to synthetic images and compare the results quantitatively with the ground truth and with images processed by other background removal algorithms. We further evaluate WBNS on real images taken with a light-sheet microscope and a super-resolution stimulated emission depletion microscope. For both cases, we compare the WBNS algorithm with hardware-based background removal techniques and present a quantitative assessment of the results. WBNS shows an excellent performance in all these applications and significantly enhances the visual appearance of fluorescence images. Moreover, it may serve as a pre-processing step for further quantitative analysis.
Highlights
Over the past decades, fluorescence microscopy has developed into a key enabling experimental technique in life sciences research
We further evaluate wavelet-based background and noise subtraction (WBNS) on real images taken with a light-sheet microscope and a super-resolution stimulated emission depletion microscope
While the largest number of emitted photons is collected by confocal microscopy, their number decreases for stimulated emission depletion (STED) imaging due to a large fraction of depletion events, which is the price to pay for the higher resolution, and even more so for stimulated emission double depletion (STEDD) due to the additional background subtraction
Summary
Fluorescence microscopy has developed into a key enabling experimental technique in life sciences research. We have further applied WBNS to real fluorescence images To this end, we have selected, on the one hand, a widefield technique with camera detection, digital scanned light sheet microscopy (DSLM) [4] and, on the other hand, a raster scanning confocal technique capable of super-resolution, namely stimulated emission depletion (STED) microscopy [5]. We have selected, on the one hand, a widefield technique with camera detection, digital scanned light sheet microscopy (DSLM) [4] and, on the other hand, a raster scanning confocal technique capable of super-resolution, namely stimulated emission depletion (STED) microscopy [5] For both modalities, hardware-based background removal techniques are available, so that we can compare the efficacy of the hardware and software solutions in a quantitative fashion. It is versatile and easy to use as it requires as input only a two-dimensional (2D) image or three-dimensional (3D) image stack plus a single additional parameter, R, the full width at half-maximum (FWHM) of the PSF, which specifies the optical resolution
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