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dc.contributor.advisorPeter Sorger.en_US
dc.contributor.authorScelfo, Tony (Tony W.)en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2007-04-03T17:08:42Z
dc.date.available2007-04-03T17:08:42Z
dc.date.copyright2006en_US
dc.date.issued2006en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/37073
dc.descriptionThesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractThe 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.en_US
dc.description.statementofresponsibilityby Tony Scelfo.en_US
dc.format.extent53 leavesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleData visualization of biological microscopy image analysesen_US
dc.typeThesisen_US
dc.description.degreeM.Eng.and S.B.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.identifier.oclc83272252en_US


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