dc.contributor.authorZhao, ZheEnen_US
dc.date.accessioned2008-09-17T09:42:58Z
dc.date.accessioned2017-07-23T08:31:35Z
dc.date.available2008-09-17T09:42:58Z
dc.date.available2017-07-23T08:31:35Z
dc.date.copyright2006en_US
dc.date.issued2006
dc.identifier.citationZhao, Z. (2006). Novel 3D statistical shape models for segmentation of medical images. Doctoral thesis, Nanyang Technological University, Singapore.
dc.identifier.urihttp://hdl.handle.net/10356/4032
dc.description.abstractThis thesis presents the development of 3D Statistical Shape Models (SSMs) for automated segmentation of 3D medical images. It also presents the automated methods for construction of Point Distribution Models (PDMs). The proposed algorithms are applied for the segmentation of 3D human brain Magnetic Resonance Images (MRIs).en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics
dc.titleNovel 3D statistical shape models for segmentation of medical imagesen_US
dc.typeThesisen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.contributor.supervisorTeoh Eam Khwang (EEE)en_US
dc.description.degreeDOCTOR OF PHILOSOPHY (EEE)en_US


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