Data visualization of biological microscopy image analyses
Name
83272252-MIT.pdf
Description
Full printable version
Size
4.53 MB
Format
Adobe PDF
Checksum (MD5)
0318fef757ffb1caa971d97c8068c469
Author(s)
Scelfo, Tony (Tony W.)
Advisor(s)
Peter Sorger.
Date Issued
2006
Publisher
Massachusetts Institute of Technology
Abstract
The Open Microscopy Environment (OME) provides biologists with a framework to store, analyze and manipulate large sets of image data. Current microscopes are capable of generating large numbers of images and when coupled with automated analysis routines, researchers are able to generate intractable sets of data. I have developed an extension to the OME toolkit, named the LoViewer, which allows researchers to quickly identify clusters of images based on relationships between analytically measured parameters. By identifying unique subsets of data, researchers are able to make use of the rest of the OME client software to view interesting images in high resolution, classify them into category groups and apply further analysis routines. The design of the LoViewer itself and its integration with the rest of the OME toolkit will be discussed in detail in body of this thesis.
Description
Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
Includes bibliographical references.
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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