Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/279735
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dc.coverage.spatialComputer aided detection methodologies for brain tumor and stroke using soft computing techniques
dc.date.accessioned2020-03-03T12:37:41Z-
dc.date.available2020-03-03T12:37:41Z-
dc.identifier.urihttp://hdl.handle.net/10603/279735-
dc.description.abstractThe abnormalities in brain cells are the main causes for forming newlinelesions in brain. These abnormal lesions in brain lead to the formation of tumors newlinein brain. Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) newlineare the two different brain image scanning methods. In this research work, MR newlineimages are used to scan the brain internal regions. Benign and Malignant are the newlinetype of abnormal lesions in brain in which, benign can be treated by radiation newlinemethods; where as malignant lesions are treated through proper surgery by newlineexpert radiologist.Tumor is defined as an uncontrolled growth of cancerous cells in any newlinepart of the body. Tumors are of different types and possess diverse newlinecharacteristics and require different treatments. At present, brain tumors are newlineclassified into primary brain tumors and metastatic or malignant brain tumors. newlineThe primary tumors begin in the brain and are inclined to stay in the brain; the newlinemetastatic or malignant tumors begin as a cancer elsewhere in the body and then newlinestart to spread into the brain region. Due to the large amount of brain tumor newlineimages that are currently being generated in the clinics, it is not possible for newlinephysicians to manually annotate and segment these images in a practical time. newlineHence, the automatic tumor detection and segmentation technique has become newlineinevitable. In conventional methods, brain tumors are detected and diagnosed newlinemanually by expert radiologist. It is time consuming and error probe process. newlineHence, it is not suitable for high population developing countries. Therefore, a newlinecomputer aided automatic brain tumor detection and diagnosis methods are newlinepreferred.In the Existing, the optimal smoothing filter and threshold methods are newlineused as tumor edge detecting approaches. The contrast agent accumulation newlinemodel and Fuzzy connectedness based intensity non uniformity correction model newlineare used as preprocessing techniques in existing methods in order to smooth newline newline
dc.format.extentxxiii, 117p.
dc.languageEnglish
dc.relationp.107-116
dc.rightsuniversity
dc.titleComputer aided detection methodologies for brain tumor and stroke using soft computing techniques
dc.title.alternative
dc.creator.researcherSivakumar P
dc.subject.keywordEngineering and Technology,Computer Science,Computer Science Information Systems
dc.subject.keywordComputer aided
dc.subject.keywordbrain tumor
dc.description.note
dc.contributor.guideGaneshkumar P
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registeredn.d.
dc.date.completed2018
dc.date.awarded30/08/2018
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File1.96 MBAdobe PDFView/Open
02_certificates.pdf1.96 MBAdobe PDFView/Open
03_abstract.pdf1.96 MBAdobe PDFView/Open
04_acknowledgements.pdf1.96 MBAdobe PDFView/Open
05_contents.pdf1.96 MBAdobe PDFView/Open
06_list of symbols and abbreviations.pdf1.96 MBAdobe PDFView/Open
07_chapter1.pdf1.97 MBAdobe PDFView/Open
08_chapter2.pdf1.97 MBAdobe PDFView/Open
09_chapter3.pdf1.97 MBAdobe PDFView/Open
10_chapter4.pdf1.97 MBAdobe PDFView/Open
11_chapter5.pdf1.97 MBAdobe PDFView/Open
12_conclusion.pdf1.96 MBAdobe PDFView/Open
13_references.pdf1.96 MBAdobe PDFView/Open
14_listofpublications.pdf1.96 MBAdobe PDFView/Open


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