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dc.contributor.authorMatthews, Harold Samuel
dc.date.accessioned2018-10-11T04:05:53Z
dc.date.available2018-10-11T04:05:53Z
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/11343/216787
dc.description© 2018 Dr. Harold Samuel Matthews
dc.description.abstractAccurate descriptions of normal craniofacial shape are essential for accurate assessment of pathologies of the craniofacial complex. Traditionally, these descriptions, have been limited to growth curves of single measurements (e.g. head circumference) to which a patient can be compared. In this thesis we exploit advances in 3D image capture and image processing and also combine tools from statistical shape analysis and multivariate statistics to produce 3D growth curves of the entire head and face. These can serve as a normative frame of reference, against which craniofacial abnormality can be judged and we demonstrate their use for assessing individual patients. They are also a tool for comparing populations, which we demonstrate by examining emerging shape differences between boys and girls throughout childhood and adolescence, and for growth prediction and age estimation. In two studies we examine the development of sex differences in craniofacial shape (craniofacial sexual dimorphism). The first compared boys and girls within a database of one year-olds. The second compared growth curves of boys and girls derived from a cross-sectional database of 3D images of children aged from 0.05-18.6 years, to examine how and when sex differences emerge. Both studies confirmed the presence of sexual dimorphism at approximately one year-old. The second also demonstrated that sexual dimorphism emerges in primarily two phases between ages five and ten and from twelve onwards. The second of these constitute the most comprehensive study of the development of sexual dimorphism to date and both studies challenge the view that sexual dimorphism emerges as the result of sex hormones at puberty. We also use the growth curves to predict the growth of individuals from 3D photographs. We validate these predictions against a sample of 50 longitudinally collected images by comparing the predicted head at the second time point to the actual head at the second time point. We also develop them into an algorithm for estimating the age of individuals from 3D photographs.en_US
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dc.subjectcraniofacial growthen_US
dc.subjectcraniofacial sexual dimorphismen_US
dc.subjectgeometric morphometricsen_US
dc.subjectage estimationen_US
dc.subjectgrowth predictionen_US
dc.subjectsynthetic growthen_US
dc.subjectclassificationen_US
dc.subject3D imagingen_US
dc.titleChanging the face of craniofacial growth curves: modelling growth and sexual dimorphism in children and adolescents using spatially dense 3D image analysisen_US
dc.typePhD thesisen_US
melbourne.affiliation.departmentPaediatrics (RCH)
melbourne.affiliation.facultyMedicine, Dentistry & Health Sciences
melbourne.affiliation.facultyMelbourne Medical School
melbourne.thesis.supervisornamePenington, Anthony
melbourne.contributor.authorMatthews, Harold Samuel
melbourne.accessrightsOpen Access


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