Title | Collaborative analysis of multi-gigapixel imaging data using Cytomine. |
Publication Type | Journal Article |
Year of Publication | 2016 |
Authors | Marée, R, Rollus, L, Stévens, B, Hoyoux, R, Louppe, G, Vandaele, R, Begon, J-M, Kainz, P, Geurts, P, Wehenkel, L |
Journal | Bioinformatics |
Volume | 32 |
Issue | 9 |
Pagination | 1395-401 |
Date Published | 2016 05 01 |
ISSN | 1367-4811 |
Keywords | Image Interpretation, Computer-Assisted, Internet, Software, Statistics as Topic |
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.beSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
DOI | 10.1093/bioinformatics/btw013 |
Alternate Journal | Bioinformatics |
PubMed ID | 26755625 |
PubMed Central ID | PMC4848407 |
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