2017
DOI: 10.12688/f1000research.11773.1
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Improved deconvolution of very weak confocal signals

Abstract: Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical section… Show more

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Cited by 14 publications
(12 citation statements)
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“…4D confocal movies were collected on a Leica SP5 or SP8 microscope using an 80 nm pixel size and a 0.25-0.30 μm Z-step interval and 20-30 optical sections, with a Z-stack collected every 0.5-2.0 s. Static images were converted to 16-bit and average projected, then range-adjusted to the minimum and maximum pixel values in ImageJ (http://rsbweb.nih.gov/ij/). To process movies, a Gaussian blur with radius 0.75 pixels was applied in ImageJ to fluorescence channels (Day et al, 2016), which were then deconvolved with Huygens Essential (Scientific Volume Imaging, Hilversum, The Netherlands) using the CMLE (Classical Maximum Likelihood Estimation) algorithm (Day et al, 2017), and then corrected for bleaching using an ImageJ plugin (cmci.embl.de/downloads/bleach_corrector). Movies were converted to hyperstacks and average projected, then range-adjusted to maximize contrast in ImageJ.…”
Section: Methods Detailsmentioning
confidence: 99%
“…4D confocal movies were collected on a Leica SP5 or SP8 microscope using an 80 nm pixel size and a 0.25-0.30 μm Z-step interval and 20-30 optical sections, with a Z-stack collected every 0.5-2.0 s. Static images were converted to 16-bit and average projected, then range-adjusted to the minimum and maximum pixel values in ImageJ (http://rsbweb.nih.gov/ij/). To process movies, a Gaussian blur with radius 0.75 pixels was applied in ImageJ to fluorescence channels (Day et al, 2016), which were then deconvolved with Huygens Essential (Scientific Volume Imaging, Hilversum, The Netherlands) using the CMLE (Classical Maximum Likelihood Estimation) algorithm (Day et al, 2017), and then corrected for bleaching using an ImageJ plugin (cmci.embl.de/downloads/bleach_corrector). Movies were converted to hyperstacks and average projected, then range-adjusted to maximize contrast in ImageJ.…”
Section: Methods Detailsmentioning
confidence: 99%
“…Huygens Essential (Scientific Volume Imaging) using the classic maximum likelihood estimation 466 algorithm (Day et al, 2017). Movies were converted to hyperstacks and average projected, then 467 range-adjusted to maximize contrast in ImageJ.…”
Section: Yeast Growth and Strain Construction 431mentioning
confidence: 99%
“…Live-cell dual-color 4D confocal imaging was performed previously described (Day et al, 2017) using a strain expressing GFP-Vig4 as an early Golgi marker and Sec7-DsRed as a late Golgi marker, with the following modifications. Cells attached to the cover glass dish surface were washed and covered with minimal SD medium.…”
Section: Fluorescence Microscopymentioning
confidence: 99%