A batch algorithm using iterative application of the Viterbi algorithm to track cells and construct cell lineages

Advances in microscope hardware in the last couple of decades have made it possible to acquire large data sets with image sequences of living cells grown in cell culture. This has led to a demand for automated ways of analyzing the acquired images. This article presents a new algorithm for tracking cells and constructing cell lineages in such image sequences. The algorithm uses information from the entire sequence to make local decisions about cell tracks and can therefore make more robust decisions than algorithms that process the data sequentially. It also incorporates image-based likelihoods of cell division and cell death into the tracking, without having to resort to separate detection algorithms or post processing of tracks. The algorithm consists of a scoring function to rank tracks and an iterative algorithm that searches for the highest scoring tracks, in a computationally efficient way, using the Viterbi algorithm.

[1]  Kenong Wu,et al.  Live cell image segmentation , 1995, IEEE Transactions on Biomedical Engineering.

[2]  Takeo Kanade,et al.  Reliable cell tracking by global data association , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[3]  Jean-Christophe Olivo-Marin,et al.  On the digital trail of mobile cells , 2006, IEEE Signal Processing Magazine.

[4]  Stanley Lemeshow,et al.  Applied Logistic Regression, Second Edition , 1989 .

[5]  Pascal Fua,et al.  Robust People Tracking with Global Trajectory Optimization , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[6]  Jr. G. Forney,et al.  The viterbi algorithm , 1973 .

[7]  S. Thrun,et al.  Substrate Elasticity Regulates Skeletal Muscle Stem Cell Self-Renewal in Culture , 2010, Science.

[8]  B. Roysam,et al.  Automated Cell Lineage Construction: A Rapid Method to Analyze Clonal Development Established with Murine Neural Progenitor Cells , 2006, Cell cycle.

[9]  Margrit Betke,et al.  Tracking of cell populations to understand their spatio-temporal behavior in response to physical stimuli , 2009, 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[10]  Takeo Kanade,et al.  Cell image analysis: Algorithms, system and applications , 2011, 2011 IEEE Workshop on Applications of Computer Vision (WACV).