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dc.contributor.authorMohd Yusof, Baharuddin
dc.date.accessioned2009-11-13T02:04:51Z
dc.date.available2009-11-13T02:04:51Z
dc.date.issued2009-10-11
dc.identifier.citationp.1A5 1 - 1A5 4en_US
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/7277
dc.descriptionOrganized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.en_US
dc.description.abstractCorpus callosum (CC) is the largest fiber bundle in human brain where it’s connected two cerebral hemispheres. Mainly, these fibers connected homologous cortical areas in nearly mirror-image sites, but a substantial number have heterotopic connections, ending in asymmetrical areas. Corpus collosum act as an integral role in relaying sensory, motor and cognitive information between homologous regions in the two cerebral hemispheres. Using MRI, corpus collosum can be discretely identified at the mid-sagittal level where it crosses the midline and its morphology has been extensively studied. Such studies have shown that the shape of the CC may be related to, handedness and certain disease such as Down’s syndrome. The purpose of this paper is to study whether incorporation of diffusion tensor imaging (DTI) and DTIbased 3D tract information can facilitate the study of anatomical parcellation of intra- corpus collosum structures. The corpus collosum is divided into six sub-regions based on trajectories into subcortical nuclei and the orbital, frontal, parietal, occipital and temporal lobes.en_US
dc.description.sponsorshipTechnical sponsored by IEEE Malaysia Sectionen_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlisen_US
dc.relation.ispartofseriesProceedings of the International Conference on Man-Machine Systems (ICoMMS 2009)en_US
dc.subjectCorpus callosumen_US
dc.subjectBrainen_US
dc.subjectDTIen_US
dc.subjectTractographen_US
dc.subjectBiomedical engineeringen_US
dc.subjectCerebral hemispheresen_US
dc.subjectCorpus callosum -- Detection systemen_US
dc.titleDetection of Corpus Collosum using DTI tractographen_US
dc.typeWorking Paperen_US


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