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Geometric morphometrics for 3D dense surface correspondence: population comparisons of shoulder bone morphology
Background: Comparisons in morphological shape/form across population groups could provide population differences that might assist in making decisions on diagnosis and prognosis by the clinician. Geometric morphometrics (GM) is one of the fields that help to provide such population comparisons....
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| Format: | Thesis |
| Language: | English |
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Department of Human Biology
2019
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| _version_ | 1867613194316414976 |
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| access_status_str | Open Access |
| author | Fouefack, Jean-Rassaire |
| author2 | Mutsvangwa, Tinashe |
| author_browse | Fouefack, Jean-Rassaire Mutsvangwa, Tinashe |
| author_facet | Mutsvangwa, Tinashe Fouefack, Jean-Rassaire |
| author_sort | Fouefack, Jean-Rassaire |
| collection | Thesis |
| description | Background: Comparisons in morphological shape/form across population groups could
provide population differences that might assist in making decisions on diagnosis and
prognosis by the clinician. Geometric morphometrics (GM) is one of the fields that help
to provide such population comparisons. In medical imaging and related disciplines, GM
is commonly done using annotated landmarks or distances measured from 3D surfaces
(consisting of triangular meshes). However, these landmarks may not be sufficient to
describe the complete shape. This project aimed to develop GM for analysis that consider
all vertices in the triangular mesh as landmarks. The developed methods were applied to
South African and Swiss shoulder bones (scapula and humerus) to analyse morphological
differences.
Methods: The developed pipeline required first establishing correspondence across the
datasets through a registration process. Gaussian process fitting was chosen to perform
the registration since it is considered state-of-the-art. Secondly, a novel method for automatic identification of vertices or areas encoding the most shape/form variation was
developed. Thirdly, a principal component analysis (PCA) that addressed the high dimensionality and lower sample size (HDLSS) phenomenon was adopted and applied to
the dense correspondence data. This approach allowed for the stabilisation of the distribution of the data in low-dimensional form/shape space. Lastly, appropriate statistical
tests were developed for population comparisons of the shoulder bones when dealing with
HDLSS data in both form and shape space.
Results: When the mesh-based GM analysis approach was applied to the training datasets
(South African and Swiss shoulder bones), it was found that the anterior glenoid which is
often the site of the shoulder dislocation is the most varied area of the glenoid. This has
implications for diagnosis and provides knowledge for prosthesis design. The distribution
of the data in the modified PCA space was shown to converge to a stable distribution when
more vertices/landmarks are used for the analysis. South African and Swiss datasets were
shown to be more distinguishable in a low-dimensional space when considering form rather
than shape. It was found that left and right South African scapula bones are significantly
different in terms of shape.
Discussion: In general, it was observed that the two populations means can be significantly
different in shape but not in form. An improved understanding of these observed shape
and form differences has utility for shoulder arthroplasty prosthesis design and may also
be useful for orthopaedic surgeons during surgical preoperative planning. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/30024 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:13.078Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Department of Human Biology |
| publisherStr | Department of Human Biology |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/30024 Geometric morphometrics for 3D dense surface correspondence: population comparisons of shoulder bone morphology Fouefack, Jean-Rassaire Mutsvangwa, Tinashe Douglas, Tania Inyang, Adijat Omowumi Biomedical Engineering Background: Comparisons in morphological shape/form across population groups could provide population differences that might assist in making decisions on diagnosis and prognosis by the clinician. Geometric morphometrics (GM) is one of the fields that help to provide such population comparisons. In medical imaging and related disciplines, GM is commonly done using annotated landmarks or distances measured from 3D surfaces (consisting of triangular meshes). However, these landmarks may not be sufficient to describe the complete shape. This project aimed to develop GM for analysis that consider all vertices in the triangular mesh as landmarks. The developed methods were applied to South African and Swiss shoulder bones (scapula and humerus) to analyse morphological differences. Methods: The developed pipeline required first establishing correspondence across the datasets through a registration process. Gaussian process fitting was chosen to perform the registration since it is considered state-of-the-art. Secondly, a novel method for automatic identification of vertices or areas encoding the most shape/form variation was developed. Thirdly, a principal component analysis (PCA) that addressed the high dimensionality and lower sample size (HDLSS) phenomenon was adopted and applied to the dense correspondence data. This approach allowed for the stabilisation of the distribution of the data in low-dimensional form/shape space. Lastly, appropriate statistical tests were developed for population comparisons of the shoulder bones when dealing with HDLSS data in both form and shape space. Results: When the mesh-based GM analysis approach was applied to the training datasets (South African and Swiss shoulder bones), it was found that the anterior glenoid which is often the site of the shoulder dislocation is the most varied area of the glenoid. This has implications for diagnosis and provides knowledge for prosthesis design. The distribution of the data in the modified PCA space was shown to converge to a stable distribution when more vertices/landmarks are used for the analysis. South African and Swiss datasets were shown to be more distinguishable in a low-dimensional space when considering form rather than shape. It was found that left and right South African scapula bones are significantly different in terms of shape. Discussion: In general, it was observed that the two populations means can be significantly different in shape but not in form. An improved understanding of these observed shape and form differences has utility for shoulder arthroplasty prosthesis design and may also be useful for orthopaedic surgeons during surgical preoperative planning. 2019-05-10T11:24:09Z 2019-05-10T11:24:09Z 2018 2019-05-07T13:05:54Z Master Thesis Masters MSc (Biomedical Engineering) http://hdl.handle.net/11427/30024 eng application/pdf Department of Human Biology Faculty of Health Sciences |
| spellingShingle | Biomedical Engineering Fouefack, Jean-Rassaire Geometric morphometrics for 3D dense surface correspondence: population comparisons of shoulder bone morphology |
| thesis_degree_str | Master's |
| title | Geometric morphometrics for 3D dense surface correspondence: population comparisons of shoulder bone morphology |
| title_full | Geometric morphometrics for 3D dense surface correspondence: population comparisons of shoulder bone morphology |
| title_fullStr | Geometric morphometrics for 3D dense surface correspondence: population comparisons of shoulder bone morphology |
| title_full_unstemmed | Geometric morphometrics for 3D dense surface correspondence: population comparisons of shoulder bone morphology |
| title_short | Geometric morphometrics for 3D dense surface correspondence: population comparisons of shoulder bone morphology |
| title_sort | geometric morphometrics for 3d dense surface correspondence population comparisons of shoulder bone morphology |
| topic | Biomedical Engineering |
| url | http://hdl.handle.net/11427/30024 |
| work_keys_str_mv | AT fouefackjeanrassaire geometricmorphometricsfor3ddensesurfacecorrespondencepopulationcomparisonsofshoulderbonemorphology |