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The ImageJ ecosystem: Open-source software for image visualization, processing, and analysis

AB. Schroeder, ETA. Dobson, CT. Rueden, P. Tomancak, F. Jug, KW. Eliceiri

. 2021 ; 30 (1) : 234-249. [pub] 20201120

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, Research Support, N.I.H., Extramural, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc21019593

Grantová podpora
P41-GM135019 NIGMS NIH HHS - United States

E-zdroje Online Plný text

NLK Free Medical Journals od 1992 do Před 1 rokem
PubMed Central od 1992 do Před 1 rokem
Europe PubMed Central od 1992 do Před 1 rokem
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Wiley Free Content od 1996 do Před 1 rokem

Odkazy

PubMed 33166005
DOI 10.1002/pro.3993
Knihovny.cz E-zdroje

For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, resulting in larger multidimensional datasets, imaging software must adapt. ImageJ is an open-source image analysis software platform that has aided researchers with a variety of image analysis applications, driven mainly by engaged and collaborative user and developer communities. The close collaboration between programmers and users has resulted in adaptations to accommodate new challenges in image analysis that address the needs of ImageJ's diverse user base. ImageJ consists of many components, some relevant primarily for developers and a vast collection of user-centric plugins. It is available in many forms, including the widely used Fiji distribution. We refer to this entire ImageJ codebase and community as the ImageJ ecosystem. Here we review the core features of this ecosystem and highlight how ImageJ has responded to imaging technology advancements with new plugins and tools in recent years. These plugins and tools have been developed to address user needs in several areas such as visualization, segmentation, and tracking of biological entities in large, complex datasets. Moreover, new capabilities for deep learning are being added to ImageJ, reflecting a shift in the bioimage analysis community towards exploiting artificial intelligence. These new tools have been facilitated by profound architectural changes to the ImageJ core brought about by the ImageJ2 project. Therefore, we also discuss the contributions of ImageJ2 to enhancing multidimensional image processing and interoperability in the ImageJ ecosystem.

Citace poskytuje Crossref.org

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