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Visualization approaches for multidimensional biological image data
Author(s) -
Curtis Rueden,
Kevin W. Eliceiri
Publication year - 2007
Publication title -
biotechniques/biotechniques
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 131
eISSN - 1940-9818
pISSN - 0736-6205
DOI - 10.2144/000112511
Subject(s) - visualization , computer science , data visualization , computational biology , image (mathematics) , artificial intelligence , biology
Effective data analysis of the modern biological microscopy data set often necessitates a variety of different analysis strategies, and this often means the biologist may need to use a combination of software tools both commercial and often-times open source. To facilitate this process, there needs to be knowledge of what the approaches are and also practical ways of sharing this data in a nonproprietary way. Thus, for users of open source and commercial software, it is important to have common approaches for multidimensional data analysis that can be run in different software packages and still be effectively compared. Projects like the Open Microscopy Environment, which aim to allow data sharing between open source client tools like ImageJ and VisBio, and commercial packages like Volocity and Imaris via the XML data model are a needed first step in providing a framework or infrastructure for microscopy analysis. As the field has gotten more quantitative in its approaches, this need has only increased with the necessity of having a way to represent key attributes of the data in an open manner.

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