ImageJ

Why we included this project

ImageJ has been a fixture in scientific image analysis for decades, and researchers in biology, microscopy, and materials labs still reach for it when they need processing they can script and reproduce rather than a black-box model. Because it is written in Java, the same code runs on Windows, macOS, and Linux, and the macro language plus plugin ecosystem make it straightforward to automate repetitive measurement, filtering, and segmentation work. It is a mature toolset for quantitative microscopy and other scientific imagery, and you do not need a machine-learning background to get useful results. It also ships as a Maven artifact, so it can be embedded directly into larger Java-based analysis pipelines. Just be aware it is a general image-processing platform, not a deep-learning framework. For most lab workflows that is a strength, not a limitation.