%0 Journal Article %J Bioinformatics %D 2016 %T Collaborative analysis of multi-gigapixel imaging data using Cytomine. %A Marée, Raphaël %A Rollus, Loïc %A Stévens, Benjamin %A Hoyoux, Renaud %A Louppe, Gilles %A Vandaele, Rémy %A Begon, Jean-Michel %A Kainz, Philipp %A Geurts, Pierre %A Wehenkel, Louis %K Image Interpretation, Computer-Assisted %K Internet %K Software %K Statistics as Topic %X

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.

%B Bioinformatics %V 32 %P 1395-401 %8 2016 05 01 %G eng %N 9 %R 10.1093/bioinformatics/btw013