LineageTracker: A statistical scoring method for tracking cell lineages in large cell populations with low temporal resolution

Proceedings - International Symposium on Biomedical Imaging

Volumn , Issue , 2011, Pages 1913-1916

  Downey, Mike ^a   Vance, Keith W ^a   Bretschneider, Till ^a  

^a UNIVERSITY OF WARWICK   (United Kingdom)

Author keywords

cell lineage profiling; cell tracking; High throughput live cell imaging

Indexed keywords

AUTOMATIC SEGMENTATIONS; C2C12 CELLS; CELL LINEAGE; CELL NUCLEUS; CELL POPULATIONS; CELL TRACKING; DATA SETS; DYNAMIC FEATURES; FLUORESCENT PROTEIN; HIGH-THROUGHPUT; HIGH-THROUGHPUT ANALYSIS; LIVE-CELL IMAGING; MULTIPLE CELLS; NON-DIVIDING CELLS; SCORING METHODS; SEGMENTATION AND TRACKING; TEMPORAL RESOLUTION; TRACKING ALGORITHM; TRACKING CELLS;

CELL CULTURE; CELL PROLIFERATION; DATA FLOW ANALYSIS; FLUORESCENCE; GENE EXPRESSION; MAMMALS; MEDICAL IMAGING; POPULATION STATISTICS; TIME SERIES;

CELLS;

EID: 80055030040     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2011.5872783     Document Type: Conference Paper

References (11)

1. Sigal, A., et al., Dynamic proteomics in individual human cells uncovers widespread cell-cycle dependence of nuclear proteins. Nature Methods, 2006. 3(7): p. 525-531.
2. Bendall, A.J. and C. Abate-Shen, Roles for Msx and Dlx homeoproteins in vertebrate development. Gene, 2000. 247(1-2): p. 17 - 31.
3. Carpenter, A.E., et al., CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biology, 2006. 7(10): p. R100.
4. Du, C.-J., et al., Interactive Segmentation of Clustered Cells via Geodesic Commute Distance and Constrained Density Weighted Nyström Method. Cytometry Part A, 2010(In Press).
5. Al-Kofahi, O., et al., Automated Cell Lineage Construction: A Rapid Method to Analyze Clonal Development Established with Murine Neural Progenitor Cells. Cell Cycle, 2006. 5(3): p. 327-335.
6. Li, K., et al., Cell population tracking and lineage construction with spatiotemporal context. Medical Image Analysis, 2008. 12(5): p. 546-566.
7. Mehnert, A. and P. Jackway, An improved seeded region growing algorithm. Pattern Recognition Letters, 1997. 18(10): p. 1065-1071.
8. Fenistein, D., et al., A fast, fully automated cell segmentation algorithm for high-throughput and high-content screening. Cytometry Part A, 2008. 73A(10): p. 958-964.
9. Loo, L.-H., et al., An approach for extensibly profiling the molecular states of cellular subpopulations. Nat Meth, 2009. 6(10): p. 759-765.
10. Murphy, R.F., M. Velliste, and G. Porreca, Robust Numerical Features for Description and Classification of Subcellular Location Patterns in Fluorescence Microscope Images. The Journal of VLSI Signal Processing, 2003. 35(3): p. 311-321.
11. Lehmussola, A., et al., Synthetic Images of High-Throughput Microscopy for Validation of Image Analysis Methods. Proceedings of the IEEE, 2008. 96(8): p. 1348-1360.