Operating system | License LGPL license | |
Developer(s) Micheal Held, Christoph Sommer, Daniel Gerlich, Qing Zhong, Bernd Fischer, Thomas Walter, Jan Ellenberg, and others (IMBA, ETHZ, EMBL Heidelberg) Initial release December 2009; 7 years ago (2009-12) Stable release 1.2.5 / January 3, 2012; 5 years ago (2012-01-03) Type Image processing & Computer vision & Machine Learning | ||
CellCognition is a free open-source computational framework for quantitative analysis of high-throughput fluorescence microscopy (time-lapse) images in the field of bioimage informatics and systems microscopy. The CellCognition framework uses image processing, computer vision and machine learning techniques for single-cell tracking and classification of cell morphologies. This enables measurements of temporal progression of cell phases, modeling of cellular dynamics and generation of phenotype map.
Contents
Features
CellCognition uses a computational pipeline which includes image segmentation, object detection, feature extraction, statistical classification, tracking of individual cells over time, detection of class-transition motifs (e.g. cells entering mitosis), and HMM correction of classification errors on class labels.
The software is a cross-platform application and runs on the three major operating systems (Microsoft Windows, Mac OS X, and Linux). It combines VIGRA based C++ computer vision library with Python based workflow engine and graphical user interface.
History
CellCognition (Version 1.0.1) was first released in December 2009 by scientists from the Gerlich Lab and the Buhmann group at the Swiss Federal Institute of Technology Zürich and the Ellenberg Lab at the European Molecular Biology Laboratory Heidelberg. The current version is 1.2.5 and being developed and maintained by the Gerlich Lab at the Institute of Molecular Biotechnology.
Application
CellCognition has been used in RNAi-based screening, applied in basic cell cycle study, and extended to unsupervised modeling.