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DeconvolutionLab2: An open-source software for deconvolution microscopy

Open access
Sage, Daniel, Donati, Lauréne, Soulez, Ferréol, Fortun, Denis, Schmit, Guillaume, Seitz, Arne, Guiet, Romain, Vonesch, Cédric, Unser, Michael·2017·Methods

Abstract

Images in fluorescence microscopy are inherently blurred due to the limit of diffraction of light. The purpose of deconvolution microscopy is to compensate numerically for this degradation. Deconvolution is widely used to restore fine details of 3D biological samples. Unfortunately, dealing with deconvolution tools is not straightforward. Among others, end users have to select the appropriate algorithm, calibration and parametrization, while potentially facing demanding computational tasks. To make deconvolution more accessible, we have developed a practical platform for deconvolution microscopy called DeconvolutionLab. Freely distributed, DeconvolutionLab hosts standard algorithms for 3D microscopy deconvolution and drives them through a user-oriented interface. In this paper, we take advantage of the release of DeconvolutionLab2 to provide a complete description of the software package and its built-in deconvolution algorithms. We examine several standard algorithms used in deconvolution microscopy, notably: Regularized inverse filter, Tikhonov regularization, Landweber, Tikhonov-Miller, Richardson-Lucy, and fast iterative shrinkage-thresholding. We evaluate these methods over large 3D microscopy images using simulated datasets and real experimental images. We distinguish the algorithms in terms of image quality, performance, usability and computational requirements. Our presentation is completed with a discussion of recent trends in deconvolution, inspired by the results of the Grand Challenge on deconvolution microscopy that was recently organized.

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Metadata

Authors
Sage, D., Donati, L., Soulez, F., Fortun, D., Schmit, G., Seitz, A., Guiet, R., Vonesch, C., & Unser, M.
Venue
Methods
Publisher
Elsevier BV
Published
2017-02
Volume
115
Pages
28-41
ISSN
1046-2023 (ISSN-L)
OpenAlex
W2568027424
Cited by
600
References
38
FWCI
18.98
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: DeconvolutionLab2: An open-source software for deconvolution microscopy. https://app.cochat.ai/papers/10.1016/j.ymeth.2016.12.015
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Sage, D., Donati, L., Soulez, F., Fortun, D., Schmit, G., Seitz, A., Guiet, R., Vonesch, C., & Unser, M. (2017). DeconvolutionLab2: An open-source software for deconvolution microscopy. Methods. https://doi.org/10.1016/j.ymeth.2016.12.015

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