Detection of infant`s cranial deformation based on spherical harmonics 3D modeling
[EN] 3D modeling is increasingly being used for the detection of infant's cranial deformation, where among other methods the deformation has been evaluated by the comparison of the cranium to an ideal cranial shape, represented by a triaxial ellipsoid. This master thesis presents an automat...
| Autor: | |
|---|---|
| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/164840 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/164840 |
| Access Level: | acceso abierto |
| Palabra clave: | Modeling Spherical harmonics Cranial deformation Infants Medicine Modelización Armónicos esféricos Deformación craneal Lactantes Medicina Modelado 3D INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA Máster Universitario en Ingeniería Geomática y Geoinformación-Màster Universitari en Enginyeria Geomàtica i Geoinformación |
| Sumario: | [EN] 3D modeling is increasingly being used for the detection of infant's cranial deformation, where among other methods the deformation has been evaluated by the comparison of the cranium to an ideal cranial shape, represented by a triaxial ellipsoid. This master thesis presents an automatic workflow to model the distances of an infant's cranium to the fitted ellipsoid with spherical harmonics and shows how the resulting spherical harmonic coefficients can be used as indicators for cranial deformation. With the model created in this thesis, the shape of a cranium can be approximated well with a linear combination of the first few spherical harmonic degrees. Furthermore, a possible indicator for plagiocephaly in infant's craniums is identified in the weight which is automatically assigned to a specific spherical harmonic. The developed workflow can be used in automatic classification tasks for the detection of cranial deformations in the future. |
|---|