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dc.contributor.advisorXiong, Zixiang
dc.creatorHua, Jianping
dc.date.accessioned2006-04-12T16:05:06Z
dc.date.available2006-04-12T16:05:06Z
dc.date.created2004-12
dc.date.issued2006-04-12
dc.identifier.urihttps://hdl.handle.net/1969.1/3244
dc.description.abstractThe image processing methodologies that have been actively studied and developed now play a very significant role in the flourishing biotechnology research. This work studies, develops and implements several image processing techniques for M-FISH and cDNA microarray images. In particular, we focus on three important areas: M-FISH image compression, microarray image processing and expression-based classification. Two schemes, embedded M-FISH image coding (EMIC) and Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis, have been introduced for M-FISH image compression and microarray image processing, respectively. In the expression-based classification area, we investigate the relationship between optimal number of features and sample size, either analytically or through simulation, for various classifiers.en
dc.format.extent1688172 bytesen
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherTexas A&M University
dc.subjectM-FISHen
dc.subjectmicroarrayen
dc.subjectimage compressionen
dc.subjectwaveleten
dc.subjectclassificationen
dc.subjectoptimal feature sizeen
dc.subjectoverfittingen
dc.titleTopics in genomic image processingen
dc.typeBooken
dc.typeThesisen
thesis.degree.departmentElectrical Engineeringen
thesis.degree.disciplineElectrical Engineeringen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameDoctor of Philosophyen
thesis.degree.levelDoctoralen
dc.contributor.committeeMemberKlappenecker, Andreas
dc.contributor.committeeMemberChan, Andrew K.
dc.contributor.committeeMemberGeorghiades, Costas N.
dc.contributor.committeeMemberDougherty, Edward R.
dc.type.genreElectronic Dissertationen
dc.type.materialtexten
dc.format.digitalOriginborn digitalen


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