@article{rueden_imagej2_2017,
	title = {{ImageJ2}: {ImageJ} for the next generation of scientific image data},
	volume = {18},
	issn = {1471-2105},
	shorttitle = {{ImageJ2}},
	url = {https://doi.org/10.1186/s12859-017-1934-z},
	doi = {10/gdsmf9},
	abstract = {ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software’s ability to handle the requirements of modern science.},
	number = {1},
	urldate = {2019-05-23},
	journal = {BMC Bioinformatics},
	author = {Rueden, Curtis T. and Schindelin, Johannes and Hiner, Mark C. and DeZonia, Barry E. and Walter, Alison E. and Arena, Ellen T. and Eliceiri, Kevin W.},
	month = nov,
	year = {2017},
	note = {00499
tex.ids: RUEDEN2017},
	pages = {529},
}

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