From Amat et al., Nature Methods, 2014*:

"The comprehensive reconstruction of cell lineages in complex multicellular organisms is a central goal of developmental biology. We present an open-source computational framework for segmentation and tracking of cell nuclei with high accuracy and speed. We demonstrate its (1) generality, by reconstructing cell lineages in four-dimensional, terabyte-sized image data of fruit-fly, zebrafish and mouse embryos, acquired with three different types of fluorescence microscopes, (2) scalability, by analyzing advanced stages of development with up to 20,000 cells per time point, at 26,000 cells min-1 on a single computer workstation, and (3) ease of use, by adjusting only two parameters across all data sets and providing visualization and editing tools for efficient data curation. Our approach achieves on average 97.0% linkage accuracy across all species and imaging modalities."

*Please cite this paper if you use this code for your research

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Intended Audience

End Users/Desktop, Science/Research

User Interface

Console/Terminal

Programming Language

C, C++

Related Categories

C++ Scientific Engineering, C++ Bio-Informatics Software, C++ Machine Learning Software, C Scientific Engineering, C Bio-Informatics Software, C Machine Learning Software

Registered

2014-06-19