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Tracking Cell Signals in Fluorescent Images

Gor, Victoria and Elowitz, Michael and Bacarian, Tigran and Mjolsness, Eric (2006) Tracking Cell Signals in Fluorescent Images. In: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), San Diego, CA, 20-25 June 2005. Vol.3. IEEE , Los Alamitos, CA, Art. No. 142. ISBN 0-7695-2372-2.

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In this paper we present the techniques for tracking cell signal in GFP (Green Fluorescent Protein) images of growing cell colonies. We use such tracking for both data extraction and dynamic modeling of intracellular processes. The techniques are based on optimization of energy functions, which simultaneously determines cell correspondences, while estimating the mapping functions. In addition to spatial mappings such as affine and Thin-Plate Spline mapping, the cell growth and cell division histories must be estimated as well. Different levels of joint optimization are discussed. The most unusual tracking feature addressed in this paper is the possibility of one-to-two correspondences caused by cell division. A novel extended softassign algorithm for solutions of one-to-many correspondences is detailed in this paper. The techniques are demonstrated on three sets of data: growing bacillus Subtillus and e-coli colonies and a developing plant shoot apical meristem. The techniques are currently used by biologists for data extraction and hypothesis formation.

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Elowitz, Michael0000-0002-1221-0967
Additional Information:© 2005 IEEE. Reprinted with permission. Posted online: 2006-01-03. This work was supported by NSF:FIBR award number EF-0330786. We are grateful to Marcus Heisler, Elliot M. Meyerowitz, Henrik Jönsson, and Joe Roden for their roles in providing test data.
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Deposited On:26 Sep 2007
Last Modified:08 Nov 2021 20:54

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