The ImageJ ecosystem is an open-source platform for biomedical image analysis, widely used by scientists for data visualization, teaching, and advanced image processing. Developed from NIH Image, ImageJ has grown due to its free availability and active user community. It allows users to modify and redistribute the software, making it accessible for scientific inquiry. ImageJ's extensibility has attracted biologists and computer scientists, enabling the development of plugins and macros for various image-processing tasks. The software supports a wide range of functions, including visualization, preprocessing, segmentation, registration, and tracking. ImageJ also facilitates collaboration through its mailing list and has inspired other projects. The ecosystem includes a variety of plugins, such as the Trainable Weka Segmentation plugin, which allows users to define object classes for segmentation. ImageJ's open-source nature has led to the creation of a diverse ecosystem, with projects like Bio-Formats, ImgLib2, and TrakEM2 contributing to its functionality. The ImageJ community has also fostered the development of other software, such as Fiji, which provides a distribution of ImageJ with additional features. ImageJ2, a newer version, aims to improve the software's ability to handle multi-dimensional data and has been supported by the NIH. The ImageJ ecosystem continues to evolve, with projects like SciJava promoting interoperability and collaboration among scientific software. The future of the ImageJ ecosystem involves further development and integration with other tools, ensuring continued support for scientific research.The ImageJ ecosystem is an open-source platform for biomedical image analysis, widely used by scientists for data visualization, teaching, and advanced image processing. Developed from NIH Image, ImageJ has grown due to its free availability and active user community. It allows users to modify and redistribute the software, making it accessible for scientific inquiry. ImageJ's extensibility has attracted biologists and computer scientists, enabling the development of plugins and macros for various image-processing tasks. The software supports a wide range of functions, including visualization, preprocessing, segmentation, registration, and tracking. ImageJ also facilitates collaboration through its mailing list and has inspired other projects. The ecosystem includes a variety of plugins, such as the Trainable Weka Segmentation plugin, which allows users to define object classes for segmentation. ImageJ's open-source nature has led to the creation of a diverse ecosystem, with projects like Bio-Formats, ImgLib2, and TrakEM2 contributing to its functionality. The ImageJ community has also fostered the development of other software, such as Fiji, which provides a distribution of ImageJ with additional features. ImageJ2, a newer version, aims to improve the software's ability to handle multi-dimensional data and has been supported by the NIH. The ImageJ ecosystem continues to evolve, with projects like SciJava promoting interoperability and collaboration among scientific software. The future of the ImageJ ecosystem involves further development and integration with other tools, ensuring continued support for scientific research.