Curtis Rueden

TL;DR: Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis that facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system.

TL;DR: ImageJ2 as mentioned in this paper is the next generation of ImageJ, which provides a host of new functionality and separates concerns, fully decoupling the data model from the user interface.

TL;DR: The entire ImageJ codebase was rewrote, 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.

TL;DR: The ImageJ project is used as a case study of how open‐source software fosters its suites of software tools, making multitudes of image‐analysis technology easily accessible to the scientific community.

TL;DR: The Trainable Weka Segmentation (TWS), a machine learning tool that leverages a limited number of manual annotations in order to train a classifier and segment the remaining data automatically, is introduced.