ImageJ2: ImageJ for the next generation of scientific image data
University of Wisconsin–Madison · Morgridge Institute for Research
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.
We rewrote the entire ImageJ codebase, engineering a redesigned plugin mechanism intended to facilitate extensibility at every level, with the goal of creating a more powerful tool that continues to serve the existing community while addressing a wider range of scientific requirements. This next-generation ImageJ, called "ImageJ2" in places where the distinction matters, provides a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace.
Citation impact
- FWCI
- 626.85
- Percentile
- 100%
- References
- 62
Authors
7- CRCurtis RuedenCorresponding
University of Wisconsin–Madison
- JSJohannes Schindelin
University of Wisconsin–Madison, Morgridge Institute for Research
- MHMark Hiner
University of Wisconsin–Madison
- BEBarry E. DeZonia
University of Wisconsin–Madison
- AEAlison E. Walter
University of Wisconsin–Madison, Morgridge Institute for Research
Topics & keywords
- Computer science
- Data science
- Image (mathematics)
- Computer graphics (images)
- Information retrieval
- Artificial intelligence
- Computer vision