Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/181051
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DC FieldValueLanguage
dc.coverage.spatialInformation and Communication Engineering
dc.date.accessioned2017-11-16T05:23:09Z-
dc.date.available2017-11-16T05:23:09Z-
dc.identifier.urihttp://hdl.handle.net/10603/181051-
dc.description.abstractAbstract available
dc.format.extentxxiii, 156p.
dc.languageEnglish US
dc.relation140-155
dc.rightsuniversity
dc.titleMRI brain tumor classification using supervised and unsupervised adaptive segmentation technique
dc.title.alternative
dc.creator.researcherV, Anitha
dc.subject.keywordAdaptive
dc.subject.keywordBrain
dc.subject.keywordRadiologic
dc.subject.keywordSegmentation
dc.subject.keywordTechnique
dc.description.noteData not available
dc.contributor.guideMurugavalli, S
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registeredn.d.
dc.date.completed2016
dc.date.awardedn.d.
dc.format.dimensions30cm.
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

Files in This Item:
File Description SizeFormat 
01_title page.pdfAttached File23.54 kBAdobe PDFView/Open
02_certificate.pdf865.58 kBAdobe PDFView/Open
03_abstract.pdf11.39 kBAdobe PDFView/Open
04_acknowledgement.pdf9.26 kBAdobe PDFView/Open
05_table of content.pdf20.48 kBAdobe PDFView/Open
06_list of table.pdf6.55 kBAdobe PDFView/Open
07_list of figures.pdf21.33 kBAdobe PDFView/Open
08_abbreviations and symbols.pdf119.84 kBAdobe PDFView/Open
09_chapter 1.pdf472.95 kBAdobe PDFView/Open
10_chapter 2.pdf235.93 kBAdobe PDFView/Open
11_chapter 3.pdf556.27 kBAdobe PDFView/Open
12_chapter 4.pdf1.23 MBAdobe PDFView/Open
13_results and conclusions.pdf143.05 kBAdobe PDFView/Open
14_references.pdf160.59 kBAdobe PDFView/Open
15_list of publication.pdf9.79 kBAdobe PDFView/Open


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