CellCognition

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CellCognition is a free, open-source software framework for analyzing high-throughput fluorescence microscopy time-lapse images. It uses image processing, computer vision, and machine learning to track single cells, measure changes in their shape and state, and build a map of cellular phenotypes over time. The workflow includes image segmentation, cell detection, feature extraction, statistical classification, tracking across frames, detecting state transitions (like entering mitosis), and correcting classification errors with a hidden Markov model. It is Python-based and runs on Windows and macOS. The project started in December 2009, with the latest stable release 1.6.1 on May 1, 2017. Developed by the Gerlich Lab at the Institute of Molecular Biotechnology, with contributions from ETH Zurich and the Ellenberg Lab at EMBL Heidelberg, CellCognition has been used for RNAi screening, basic cell cycle studies, and unsupervised modeling. More information at cellcognition-project.org. License: LGPL.