napari-imagej: ImageJ Ecosystem Access from napari

The Python image processing community has seen rapid growth from new members across many domains and with varying levels of software proficiency. Much of this growth is driven by the accessibility of the scientific Python software stack. The napari application for n-dimensional image visualization and analysis can potentially further this growth by fulfilling the need for a convenient and powerful graphical interface built atop these technologies. The plugin-based model of napari promotes extensibility, sharing, and modularity, and the rapidly growing napari community is doing an excellent job driving the development of needed features to accelerate and broaden napari’s utility. Meanwhile, the ImageJ software ecosystem, beginning with the original ImageJ and now supported by ImageJ2 and Fiji, has developed over decades into a flourishing community for n-dimensional image processing in Java. This maturity makes the ImageJ ecosystem a prime candidate for collaboration, and there is already demand from napari users for popular ImageJ functions. While some ImageJ features have been or will be ported to napari, this approach cannot practically scale throughout the entire ImageJ ecosystem. A direct port would significantly increase the maintenance burden on developers, distracting from work that might address new problems in the napari community. A more ideal solution would be for napari and ImageJ to integrate directly, removing the need to keep plugin ports in sync between the two.

Nature Methods, 20(10), 1443-1444