@inproceedings {408,
	title = {A statistical thresholding method for cell tracking},
	booktitle = {2006 IEEE International Symposium on Signal Processing and Information Technology},
	year = {2006},
	abstract = {<p>Tracking the motion of cells in culture is a task, which often still Is undertaken manually, and for which automated methods are strongly desirable. Researchers visually perform cell motion analysis, observe cell movements and cell shape changes for hours to discover when, where and how fast It moves, splits or dies. Hematopoletlc stem cells (HSCs) proliferate and differentiate to different blood cell types continuously during their lifetime, and are of substantial interest in gene therapy, cancer, and stem-cell research. In this paper a statistical method is introduced to track HSCs over time. A statistical thresholding method is combined with joint probabilistic data association in the proposed HSC tracker</p>
},
	keywords = {blood, blood cell, cancer, cell motion analysis, cell tracking, cellular biophysics, gene therapy, hematopoletlc stem cells proliferate, image motion analysis, image segmentation, medical image processing, statistical analysis, statistical thresholding method, stem-cell research},
	doi = {http://dx.doi.org/10.1109/ISSPIT.2006.270801},
	author = {J Ramunas and N Nezamoddin Kachouie and P Fieguth and E Jervis}
}
