Computational image analysis of subcellular dynamics in time-lapse fluorescence microscopy
Name
60678461-MIT.pdf
Description
Full printable version
Size
6.87 MB
Format
Adobe PDF
Checksum (MD5)
84833c662183c6cc34342f0a268a7eac
Author(s)
Huang, Austin V., 1980-
Advisor(s)
Tomas Lozano-Perez.
Date Issued
2005
Publisher
Massachusetts Institute of Technology
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).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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