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Proceedings Paper

The Open Microscopy Environment: open image informatics for the biological sciences
Author(s): Colin Blackburn; Chris Allan; Sébastien Besson; Jean-Marie Burel; Mark Carroll; Richard K. Ferguson; Helen Flynn; David Gault; Kenneth Gillen; Roger Leigh; Simone Leo; Simon Li; Dominik Lindner; Melissa Linkert; Josh Moore; William J. Moore; Balaji Ramalingam; Emil Rozbicki; Gabriella Rustici; Aleksandra Tarkowska; Petr Walczysko; Eleanor Williams; Jason R. Swedlow
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Paper Abstract

Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. While the open FITS file format is ubiquitous in astronomy, astronomical imaging shares many challenges with biological imaging, including the need to share large image sets using secure, cross-platform APIs, and the need for scalable applications for processing and visualization. The Open Microscopy Environment (OME) is an open-source software framework developed to address these challenges. OME tools include: an open data model for multidimensional imaging (OME Data Model); an open file format (OME-TIFF) and library (Bio-Formats) enabling free access to images (5D+) written in more than 145 formats from many imaging domains, including FITS; and a data management server (OMERO). The Java-based OMERO client-server platform comprises an image metadata store, an image repository, visualization and analysis by remote access, allowing sharing and publishing of image data. OMERO provides a means to manage the data through a multi-platform API. OMERO’s model-based architecture has enabled its extension into a range of imaging domains, including light and electron microscopy, high content screening, digital pathology and recently into applications using non-image data from clinical and genomic studies. This is made possible using the Bio-Formats library. The current release includes a single mechanism for accessing image data of all types, regardless of original file format, via Java, C/C++ and Python and a variety of applications and environments (e.g. ImageJ, Matlab and R).

Paper Details

Date Published: 26 July 2016
PDF: 8 pages
Proc. SPIE 9913, Software and Cyberinfrastructure for Astronomy IV, 991324 (26 July 2016); doi: 10.1117/12.2232291
Show Author Affiliations
Colin Blackburn, Univ. of Dundee (United Kingdom)
Chris Allan, Glencoe Software, Inc. (United States)
Sébastien Besson, Univ. of Dundee (United Kingdom)
Jean-Marie Burel, Univ. of Dundee (United Kingdom)
Mark Carroll, Univ. of Dundee (United Kingdom)
Richard K. Ferguson, Univ. of Dundee (United Kingdom)
Helen Flynn, Univ. of Dundee (United Kingdom)
David Gault, Univ. of Dundee (United Kingdom)
Kenneth Gillen, Univ. of Dundee (United Kingdom)
Roger Leigh, Univ. of Dundee (United Kingdom)
Simone Leo, Univ. of Dundee (United Kingdom)
Simon Li, Univ. of Dundee (United Kingdom)
Dominik Lindner, Univ. of Dundee (United Kingdom)
Melissa Linkert, Glencoe Software, Inc. (United States)
Josh Moore, Univ. of Dundee (United Kingdom)
Glencoe Software, Inc. (United Kingdom)
William J. Moore, Univ. of Dundee (United Kingdom)
Balaji Ramalingam, Univ. of Dundee (United Kingdom)
Emil Rozbicki, Glencoe Software, Inc. (United States)
Gabriella Rustici, Univ. of Dundee (United Kingdom)
Aleksandra Tarkowska, Univ. of Dundee (United Kingdom)
Petr Walczysko, Univ. of Dundee (United Kingdom)
Eleanor Williams, Univ. of Dundee (United Kingdom)
Jason R. Swedlow, Univ. of Dundee (United Kingdom)
Glencoe Software, Inc. (United States)

Published in SPIE Proceedings Vol. 9913:
Software and Cyberinfrastructure for Astronomy IV
Gianluca Chiozzi; Juan C. Guzman, Editor(s)

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