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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 sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal of background noise. This approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage.

SUBMITTER: Day KJ

PROVIDER: S-EPMC5553083 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Improved deconvolution of very weak confocal signals.

Day Kasey J KJ La Rivière Patrick J PJ Chandler Talon T Bindokas Vytas P VP Ferrier Nicola J NJ Glick Benjamin S BS

F1000Research 20170606

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 ...[more]

PMID: 28868135

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