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An interactive ImageJ plugin for semi-automated image denoising in electron microscopy

Joris Roels (UGent) , Frank Vernaillen, Anna Kremer (UGent) , Amanda Gonçalves (UGent) , Jan Aelterman (UGent) , Hiep Luong (UGent) , Bart Goossens (UGent) , Wilfried Philips (UGent) , Saskia Lippens (UGent) and Yvan Saeys (UGent)
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Abstract
The recent advent of 3D in electron microscopy (EM) has allowed for detection of nanometer resolution structures. This has caused an explosion in dataset size, necessitating the development of automated workflows. Moreover, large 3D EM datasets typically require hours to days to be acquired and accelerated imaging typically results in noisy data. Advanced denoising techniques can alleviate this, but tend to be less accessible to the community due to low-level programming environments, complex parameter tuning or a computational bottleneck. We present DenoisEM: an interactive and GPU accelerated denoising plugin for ImageJ that ensures fast parameter tuning and processing through parallel computing. Experimental results show that DenoisEM is one order of magnitude faster than related software and can accelerate data acquisition by a factor of 4 without significantly affecting data quality. Lastly, we show that image denoising benefits visualization and (semi-)automated segmentation and analysis of ultrastructure in various volume EM datasets.
Keywords
FREQUENCY LOCALIZATION, QUANTITATIVE-ANALYSIS, FILTER, DECONVOLUTION, TRANSFORM, CELL, SEM

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MLA
Roels, Joris, et al. “An Interactive ImageJ Plugin for Semi-Automated Image Denoising in Electron Microscopy.” NATURE COMMUNICATIONS, vol. 11, no. 1, 2020, doi:10.1038/s41467-020-14529-0.
APA
Roels, J., Vernaillen, F., Kremer, A., Gonçalves, A., Aelterman, J., Luong, H., … Saeys, Y. (2020). An interactive ImageJ plugin for semi-automated image denoising in electron microscopy. NATURE COMMUNICATIONS, 11(1). https://doi.org/10.1038/s41467-020-14529-0
Chicago author-date
Roels, Joris, Frank Vernaillen, Anna Kremer, Amanda Gonçalves, Jan Aelterman, Hiep Luong, Bart Goossens, Wilfried Philips, Saskia Lippens, and Yvan Saeys. 2020. “An Interactive ImageJ Plugin for Semi-Automated Image Denoising in Electron Microscopy.” NATURE COMMUNICATIONS 11 (1). https://doi.org/10.1038/s41467-020-14529-0.
Chicago author-date (all authors)
Roels, Joris, Frank Vernaillen, Anna Kremer, Amanda Gonçalves, Jan Aelterman, Hiep Luong, Bart Goossens, Wilfried Philips, Saskia Lippens, and Yvan Saeys. 2020. “An Interactive ImageJ Plugin for Semi-Automated Image Denoising in Electron Microscopy.” NATURE COMMUNICATIONS 11 (1). doi:10.1038/s41467-020-14529-0.
Vancouver
1.
Roels J, Vernaillen F, Kremer A, Gonçalves A, Aelterman J, Luong H, et al. An interactive ImageJ plugin for semi-automated image denoising in electron microscopy. NATURE COMMUNICATIONS. 2020;11(1).
IEEE
[1]
J. Roels et al., “An interactive ImageJ plugin for semi-automated image denoising in electron microscopy,” NATURE COMMUNICATIONS, vol. 11, no. 1, 2020.
@article{8651412,
  abstract     = {The recent advent of 3D in electron microscopy (EM) has allowed for detection of nanometer resolution structures. This has caused an explosion in dataset size, necessitating the development of automated workflows. Moreover, large 3D EM datasets typically require hours to days to be acquired and accelerated imaging typically results in noisy data. Advanced denoising techniques can alleviate this, but tend to be less accessible to the community due to low-level programming environments, complex parameter tuning or a computational bottleneck. We present DenoisEM: an interactive and GPU accelerated denoising plugin for ImageJ that ensures fast parameter tuning and processing through parallel computing. Experimental results show that DenoisEM is one order of magnitude faster than related software and can accelerate data acquisition by a factor of 4 without significantly affecting data quality. Lastly, we show that image denoising benefits visualization and (semi-)automated segmentation and analysis of ultrastructure in various volume EM datasets.},
  articleno    = {771},
  author       = {Roels, Joris and Vernaillen, Frank and Kremer, Anna and Gonçalves, Amanda and Aelterman, Jan and Luong, Hiep and Goossens, Bart and Philips, Wilfried and Lippens, Saskia and Saeys, Yvan},
  issn         = {2041-1723},
  journal      = {NATURE COMMUNICATIONS},
  keywords     = {FREQUENCY LOCALIZATION,QUANTITATIVE-ANALYSIS,FILTER,DECONVOLUTION,TRANSFORM,CELL,SEM},
  language     = {eng},
  number       = {1},
  pages        = {13},
  title        = {An interactive ImageJ plugin for semi-automated image denoising in electron microscopy},
  url          = {http://dx.doi.org/10.1038/s41467-020-14529-0},
  volume       = {11},
  year         = {2020},
}

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