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ImageJ2: ImageJ for the next generation of scientific image data.

Curtis T RuedenJohannes SchindelinMark C HinerBarry E DeZoniaAlison E WalterEllen T ArenaKevin W Eliceiri
Published in: BMC bioinformatics (2017)
Scientific imaging benefits from open-source programs that advance new method development and deployment to a diverse audience. ImageJ has continuously evolved with this idea in mind; however, new and emerging scientific requirements have posed corresponding challenges for ImageJ's development. The described improvements provide a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs. Future efforts will focus on implementing new algorithms in this framework and expanding collaborations with other popular scientific software suites.
Keyphrases
  • current status
  • deep learning
  • machine learning
  • high resolution
  • quality improvement
  • public health
  • electronic health record
  • big data
  • data analysis