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ilastik is an interactive machine learning software tool for (bio)image analysis, developed and published by the ilastik project team. Designed as a simple and user-friendly application, it enables interactive image classification, segmentation, and analysis without requiring any prior experience in image processing, making it accessible to researchers and practitioners across the biological and biomedical imaging communities. The software belongs to the image analysis and machine learning category, with particular relevance for scientific and bioimaging workflows. The current version available in this catalog is 1.3.0, which is the single release listed. ilastik is built as a modular software framework that supports a range of specialized workflows. These include automated, supervised pixel-level and object-level classification, automated and semi-automated object tracking, semi-automated segmentation, and object counting without detection. This modular design allows users to select the workflow that matches their analysis task while relying on the same underlying interactive machine learning approach, in which user annotations guide the classification process. A defining characteristic of ilastik is its lazy evaluation model: most analysis operations are performed lazily, which enables targeted interactive processing of data subvolumes. Users can interactively refine results on selected regions of large datasets, and once the model is sufficiently trained, complete volume analysis can be carried out in offline batch mode. This combination of interactivity and batch processing makes ilastik suitable for handling large multidimensional image data efficiently, supporting both exploratory analysis and full-scale automated processing. Typical use cases for ilastik include segmenting cells, tissues, or subcellular structures in microscopy images, classifying pixels or detected objects into biologically meaningful categories, tracking objects across time-lapse recordings, and counting objects without explicit detection steps. By combining an accessible interface with supervised machine learning and scalable processing, ilastik serves as a practical tool for interactive (bio)image analysis tasks.
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