@article {1288, title = {Collaborative analysis of multi-gigapixel imaging data using Cytomine.}, journal = {Bioinformatics}, volume = {32}, year = {2016}, month = {2016 05 01}, pages = {1395-401}, 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.

}, keywords = {Image Interpretation, Computer-Assisted, Internet, Software, Statistics as Topic}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btw013}, author = {Mar{\'e}e, Rapha{\"e}l and Rollus, Lo{\"\i}c and St{\'e}vens, Benjamin and Hoyoux, Renaud and Louppe, Gilles and Vandaele, R{\'e}my and Begon, Jean-Michel and Kainz, Philipp and Geurts, Pierre and Wehenkel, Louis} }