Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/332789
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dc.coverage.spatialSome investigations on human knee elbow and shoulder images using finite element modelling and soft computing techniques
dc.date.accessioned2021-07-20T10:03:07Z-
dc.date.available2021-07-20T10:03:07Z-
dc.identifier.urihttp://hdl.handle.net/10603/332789-
dc.description.abstractThe finite element modelling (FEM) is a powerful instrument to study articular and tissue mechanics, as it allows variables to be manipulated and situations simulated which are difficult or impossible to evaluate clinically or experimentally. The accuracy of FE models depends on well-defined anatomy, material properties and limits. Due to the significant inter-tissue structural variability in morphology, analysis of individual and insights tends to newlineinvolve a subject- specific FE modelling. Modelling efforts in in vivo were limited by difficulties in data acquisition and multimodal data analysis, including proper registration and integration of data, in finite element model construction or validation. Recent, several techniques have increased the potential to incorporate accurate tissue boundaries and morphology for image reconstruction based on subject specific finite element analysis. Hence, the proposed system uses image segmentation with 3D FEM uses the concept of image segmentation of medical images. The proposed system uses canny edge detection or improved canny edge detection for the segmentation of medical images. The canny edge method extracts the edge information of MR images of knee cartilage by incorporating a vector image model. The study also uses certain noise removal models at its pre-processing stage to remove the presence of Rician noise in MRI. Finally, the obtained segmented edges is sent as input to the 3D conversion in Ansys. The ground truth information is collected from the skilled doctors, who are experts in knee. newline newline
dc.format.extentxv,106 p.
dc.languageEnglish
dc.relationp.96-105
dc.rightsuniversity
dc.titleSome investigations on human knee elbow and shoulder images using finite element modelling and soft computing techniques
dc.title.alternative
dc.creator.researcherBuvanesvari, V K
dc.subject.keywordClinical Pre Clinical and Health
dc.subject.keywordClinical Medicine
dc.subject.keywordMedicine General and Internal
dc.subject.keywordHuman Knee
dc.subject.keywordElbow and Shoulder
dc.subject.keywordSoft Computing
dc.description.note
dc.contributor.guideSuganthi, M
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Science and Humanities
dc.date.registered
dc.date.completed2020
dc.date.awarded2020
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Science and Humanities

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01_title.pdfAttached File23.01 kBAdobe PDFView/Open
02_certificates.pdf1.7 MBAdobe PDFView/Open
04_bonafidecertificate.pdf100.14 kBAdobe PDFView/Open
05_abstracts.pdf57.51 kBAdobe PDFView/Open
06_acknowledgements.pdf67.02 kBAdobe PDFView/Open
07_contents.pdf76.07 kBAdobe PDFView/Open
08_listoftables.pdf55.69 kBAdobe PDFView/Open
09_listoffigures.pdf75.89 kBAdobe PDFView/Open
10_listofabbreviations.pdf346.15 kBAdobe PDFView/Open
11_chapter1.pdf437.79 kBAdobe PDFView/Open
12_chapter2.pdf232.88 kBAdobe PDFView/Open
13_chapter3.pdf554.21 kBAdobe PDFView/Open
14_chapter4.pdf834.8 kBAdobe PDFView/Open
15_chapter5.pdf335.89 kBAdobe PDFView/Open
16_conclusion.pdf71.77 kBAdobe PDFView/Open
17_references.pdf163.54 kBAdobe PDFView/Open
18_listofpublications.pdf81.91 kBAdobe PDFView/Open
80_recommendation.pdf173.68 kBAdobe PDFView/Open


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