2026-09-19T11:16:52Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/301722022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Tomas Lozano-Perez.
Huang, Austin V., 1980-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2006-03-24T18:26:18Z
2006-03-24T18:26:18Z
2004
2005
http://hdl.handle.net/1721.1/30172
60678461
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2005.
Includes bibliographical references (p. 69-73).
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.
by Austin V. Huang.
S.M.
73 p.
3484651 bytes
3492246 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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
Electrical Engineering and Computer Science.
Computational image analysis of subcellular dynamics in time-lapse fluorescence microscopy
Thesis
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