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DeepImageJ: A user-friendly plugin to run deep learning models in ImageJ

View ORCID ProfileEstibaliz Gómez-de-Mariscal, Carlos García-López-de-Haro, Laurène Donati, Michael Unser, View ORCID ProfileArrate Muñoz-Barrutia, Daniel Sage
doi: https://doi.org/10.1101/799270
Estibaliz Gómez-de-Mariscal
1Bioengineering and Aerospace Engineering Department, Universidad Carlos III de Madrid and Instituto de Investigación Sanitaria, Gregorio Marañón, Spain
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  • ORCID record for Estibaliz Gómez-de-Mariscal
Carlos García-López-de-Haro
1Bioengineering and Aerospace Engineering Department, Universidad Carlos III de Madrid and Instituto de Investigación Sanitaria, Gregorio Marañón, Spain
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Laurène Donati
2Biomedical Imaging Group, École polytechnique fédérale, de Lausanne (EPFL), Switzerland
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Michael Unser
2Biomedical Imaging Group, École polytechnique fédérale, de Lausanne (EPFL), Switzerland
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Arrate Muñoz-Barrutia
1Bioengineering and Aerospace Engineering Department, Universidad Carlos III de Madrid and Instituto de Investigación Sanitaria, Gregorio Marañón, Spain
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  • For correspondence: mamunozb@ing.uc3m.es daniel.sage@epfl.ch
Daniel Sage
2Biomedical Imaging Group, École polytechnique fédérale, de Lausanne (EPFL), Switzerland
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  • For correspondence: mamunozb@ing.uc3m.es daniel.sage@epfl.ch
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ABSTRACT

DeepImageJ is a user-friendly plugin that enables the generic use in FIJI/ImageJ of pre-trained deep learning (DL) models provided by their developers. The plugin acts as a software layer between TensorFlow and FIJI/ImageJ, runs on a standard CPU-based computer and can be used without any DL expertise. Beyond its direct use, we expect DeepImageJ to contribute to the spread and assessment of DL models in life-sciences applications and bioimage informatics.

Footnotes

  • Correction of author-name

  • https://deepimagej.github.io/deepimagej/

  • ↵9 https://deepimagej.github.io/deepimagej/

  • ↵10 https://imagejdocu.tudor.lu/faq/technical/how_do_i_increase_the_memory_in_imagej

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted October 17, 2019.
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DeepImageJ: A user-friendly plugin to run deep learning models in ImageJ
Estibaliz Gómez-de-Mariscal, Carlos García-López-de-Haro, Laurène Donati, Michael Unser, Arrate Muñoz-Barrutia, Daniel Sage
bioRxiv 799270; doi: https://doi.org/10.1101/799270
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DeepImageJ: A user-friendly plugin to run deep learning models in ImageJ
Estibaliz Gómez-de-Mariscal, Carlos García-López-de-Haro, Laurène Donati, Michael Unser, Arrate Muñoz-Barrutia, Daniel Sage
bioRxiv 799270; doi: https://doi.org/10.1101/799270

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