Development of a statistical shape and appearance model of the skull from a South African population

dc.contributor.advisorMutsvangwa, Tinashe
dc.contributor.advisorDouglas, Tania
dc.contributor.authorLugadilu, Brian
dc.date.accessioned2019-01-31T09:59:34Z
dc.date.available2019-01-31T09:59:34Z
dc.date.issued2018
dc.date.updated2019-01-31T09:47:17Z
dc.description.abstractStatistical shape models (SSMs) and statistical appearance models (SAMs) have been applied in medical analysis such as in surgical planning, finite element analysis, model-based segmentation, and in the fields of anthropometry and forensics. Similar applications can make use of SSMs and SAMs of the skull. A combination of the SSM and SAM of the skull can also be used in model-based segmentation. This document presents the development of a SSM and a SAM of the human skull from a South African population, using the Scalismo software package. The SSM development pipeline was composed of three steps: 1) Image data segmentation and processing; 2) Development of a free-form deformation (FFD) model for establishing correspondence across the training dataset; and 3) Development and validation of a SSM from the corresponding dataset. The SSM was validated using the leave one-out cross-validation method. The first eight principal components of the SSM represented 92.13% of the variation in the model. The generality of the model in terms of the Hausdorff distance between a new shape generated by the SSM and instances of the SSM had a steady state value of 1.48mm. The specificity of the model (in terms of Hausdorff distance) had a steady state value of 2.04mm. The SAM development pipeline involved four steps: 1) Volumetric mesh generation of the reference mesh to be used in establishing volumetric correspondence; 2) Sampling of intensity values from original computed tomography (CT) images using the in-correspondence volumetric meshes; and 3) Development of a SAM from the in-correspondence intensity values. A complete validation of the SAM was not possible due to limitations of the Scalismo software. As a result, only the shapes of the incomplete skulls were reconstructed and thereby validated. The amount of missing detail, as represented by absent landmarks, affected the registration results. Complete validation of the SAM is recommended as future work, via the use of a combined shape and intensity model (SSIM).
dc.identifier.apacitationLugadilu, B. (2018). <i>Development of a statistical shape and appearance model of the skull from a South African population</i>. (). University of Cape Town ,Faculty of Health Sciences ,Division of Biomedical Engineering. Retrieved from http://hdl.handle.net/11427/29187en_ZA
dc.identifier.chicagocitationLugadilu, Brian. <i>"Development of a statistical shape and appearance model of the skull from a South African population."</i> ., University of Cape Town ,Faculty of Health Sciences ,Division of Biomedical Engineering, 2018. http://hdl.handle.net/11427/29187en_ZA
dc.identifier.citationLugadilu, B. 2018. Development of a statistical shape and appearance model of the skull from a South African population. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Lugadilu, Brian AB - Statistical shape models (SSMs) and statistical appearance models (SAMs) have been applied in medical analysis such as in surgical planning, finite element analysis, model-based segmentation, and in the fields of anthropometry and forensics. Similar applications can make use of SSMs and SAMs of the skull. A combination of the SSM and SAM of the skull can also be used in model-based segmentation. This document presents the development of a SSM and a SAM of the human skull from a South African population, using the Scalismo software package. The SSM development pipeline was composed of three steps: 1) Image data segmentation and processing; 2) Development of a free-form deformation (FFD) model for establishing correspondence across the training dataset; and 3) Development and validation of a SSM from the corresponding dataset. The SSM was validated using the leave one-out cross-validation method. The first eight principal components of the SSM represented 92.13% of the variation in the model. The generality of the model in terms of the Hausdorff distance between a new shape generated by the SSM and instances of the SSM had a steady state value of 1.48mm. The specificity of the model (in terms of Hausdorff distance) had a steady state value of 2.04mm. The SAM development pipeline involved four steps: 1) Volumetric mesh generation of the reference mesh to be used in establishing volumetric correspondence; 2) Sampling of intensity values from original computed tomography (CT) images using the in-correspondence volumetric meshes; and 3) Development of a SAM from the in-correspondence intensity values. A complete validation of the SAM was not possible due to limitations of the Scalismo software. As a result, only the shapes of the incomplete skulls were reconstructed and thereby validated. The amount of missing detail, as represented by absent landmarks, affected the registration results. Complete validation of the SAM is recommended as future work, via the use of a combined shape and intensity model (SSIM). DA - 2018 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2018 T1 - Development of a statistical shape and appearance model of the skull from a South African population TI - Development of a statistical shape and appearance model of the skull from a South African population UR - http://hdl.handle.net/11427/29187 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/29187
dc.identifier.vancouvercitationLugadilu B. Development of a statistical shape and appearance model of the skull from a South African population. []. University of Cape Town ,Faculty of Health Sciences ,Division of Biomedical Engineering, 2018 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/29187en_ZA
dc.language.isoeng
dc.publisher.departmentDivision of Biomedical Engineering
dc.publisher.facultyFaculty of Health Sciences
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherBiomedical Engineering
dc.titleDevelopment of a statistical shape and appearance model of the skull from a South African population
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMSc (Med)
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