| RUBENS, Ulysse, Romain MORMONT, Lassi PAAVOLAINEN, Volker BÄCKER, Benjamin PAVIE, Leandro A. SCHOLZ, Gino MICHIELS, Martin MAŠKA, Devrim ÜNAY, Graeme BALL, Renaud HOYOUX, Rémy VANDAELE, Ofra GOLANI, Stefan G. STANCIU, Natasa SLADOJE, Perrine PAUL-GILLOTEAUX, Raphaël MARÉE and Sébastien TOSI. BIAFLOWS: A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows. Patterns. Cell Press, 2020, vol. 1, No 3, p. 1-10. ISSN 2666-3899. Available from: https://dx.doi.org/10.1016/j.patter.2020.100040. |
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@article{1661361,
author = {Rubens, Ulysse and Mormont, Romain and Paavolainen, Lassi and Bäcker, Volker and Pavie, Benjamin and Scholz, Leandro A. and Michiels, Gino and Maška, Martin and Ünay, Devrim and Ball, Graeme and Hoyoux, Renaud and Vandaele, Rémy and Golani, Ofra and Stanciu, Stefan G. and Sladoje, Natasa and PaulandGilloteaux, Perrine and Marée, Raphaël and Tosi, Sébastien},
article_number = {3},
doi = {http://dx.doi.org/10.1016/j.patter.2020.100040},
keywords = {image analysis; software benchmarking; deployment; reproducibility; bioimaging; deep learning},
language = {eng},
issn = {2666-3899},
journal = {Patterns},
title = {BIAFLOWS: A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows},
url = {http://dx.doi.org/10.1016/j.patter.2020.100040},
volume = {1},
year = {2020}
}
TY - JOUR
ID - 1661361
AU - Rubens, Ulysse - Mormont, Romain - Paavolainen, Lassi - Bäcker, Volker - Pavie, Benjamin - Scholz, Leandro A. - Michiels, Gino - Maška, Martin - Ünay, Devrim - Ball, Graeme - Hoyoux, Renaud - Vandaele, Rémy - Golani, Ofra - Stanciu, Stefan G. - Sladoje, Natasa - Paul-Gilloteaux, Perrine - Marée, Raphaël - Tosi, Sébastien
PY - 2020
TI - BIAFLOWS: A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows
JF - Patterns
VL - 1
IS - 3
SP - 1-10
EP - 1-10
PB - Cell Press
SN - 26663899
KW - image analysis
KW - software benchmarking
KW - deployment
KW - reproducibility
KW - bioimaging
KW - deep learning
UR - http://dx.doi.org/10.1016/j.patter.2020.100040
N2 - Image analysis is key to extracting quantitative information from scientific microscopy images, but the methods involved are now often so refined that they can no longer be unambiguously described by written protocols. We introduce BIAFLOWS, an open-source web tool enabling to reproducibly deploy and benchmark bioimage analysis workflows coming from any software ecosystem. A curated instance of BIAFLOWS populated with 34 image analysis workflows and 15 microscopy image datasets recapitulating common bioimage analysis problems is available online. The workflows can be launched and assessed remotely by comparing their performance visually and according to standard benchmark metrics. We illustrated these features by comparing seven nuclei segmentation workflows, including deep-learning methods. BIAFLOWS enables to benchmark and share bioimage analysis workflows, hence safeguarding research results and promoting high-quality standards in image analysis. The platform is thoroughly documented and ready to gather annotated microscopy datasets and workflows contributed by the bioimaging community.
ER -
RUBENS, Ulysse, Romain MORMONT, Lassi PAAVOLAINEN, Volker BÄCKER, Benjamin PAVIE, Leandro A. SCHOLZ, Gino MICHIELS, Martin MAŠKA, Devrim ÜNAY, Graeme BALL, Renaud HOYOUX, Rémy VANDAELE, Ofra GOLANI, Stefan G. STANCIU, Natasa SLADOJE, Perrine PAUL-GILLOTEAUX, Rapha$\backslash$''el MARÉE and Sébastien TOSI. BIAFLOWS: A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows. \textit{Patterns}. Cell Press, 2020, vol.~1, No~3, p.~1-10. ISSN~2666-3899. Available from: https://dx.doi.org/10.1016/j.patter.2020.100040.
|
