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Computational image analysis of subcellular dynamics in time-lapse fluorescence microscopy

Author(s)
Huang, Austin V., 1980-
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Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Tomas Lozano-Perez.
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M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
The use of image segmentation and motion tracking algorithms was adapted for analyzing time-lapse data of cells with fluorescently labeled protein. Performance metrics were devised and algorithm parameters were matched to hand-created ground-truth data. The performance of these algorithms in this domain was compared. Finally, the optimal algorithms were selected and used to acquire statistics on existing data, in order to reproduce previous studies on the cell cytoskeleton. New data was acquired to extend previous results and further test the algorithms on a different cell line, under both widefield and confocal microscope conditions.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2005.
 
Includes bibliographical references (p. 69-73).
 
Date issued
2005
URI
http://hdl.handle.net/1721.1/30172
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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