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Bioinformatics. 2016 May 1;32(9):1395-401. doi: 10.1093/bioinformatics/btw013. Epub 2016 Jan 10.

Collaborative analysis of multi-gigapixel imaging data using Cytomine.

Author information

1
Systems and Modeling, Department of Electrical Engineering and Computer Science and GIGA-Research, University of Liège, Liège, Belgium Bioimage Analysis Unit, Institut Pasteur, Paris, France.
2
Systems and Modeling, Department of Electrical Engineering and Computer Science and GIGA-Research, University of Liège, Liège, Belgium.
3
Institute of Biophysics, Medical University of Graz, Graz, Austria.

Abstract

MOTIVATION:

Collaborative analysis of massive imaging datasets is essential to enable scientific discoveries.

RESULTS:

We developed Cytomine to foster active and distributed collaboration of multidisciplinary teams for large-scale image-based studies. It uses web development methodologies and machine learning in order to readily organize, explore, share and analyze (semantically and quantitatively) multi-gigapixel imaging data over the internet. We illustrate how it has been used in several biomedical applications.

AVAILABILITY AND IMPLEMENTATION:

Cytomine (http://www.cytomine.be/) is freely available under an open-source license from http://github.com/cytomine/ A documentation wiki (http://doc.cytomine.be) and a demo server (http://demo.cytomine.be) are also available.

CONTACT:

info@cytomine.be

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
26755625
PMCID:
PMC4848407
DOI:
10.1093/bioinformatics/btw013
[Indexed for MEDLINE]
Free PMC Article

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