A statistical dynamic cardiac atlas for the virtual physiological human: construction and application
This thesis is centered on the construction of a cardiac atlas to serve as a common reference frame in the Virtual Physiological Human (VPH). The construction covers the entire construction pipeline, starting from a set of 3D+t multislice computed tomography images, then performing a spatial normali...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/132632 |
| Acceso en línea: | http://hdl.handle.net/10803/132632 |
| Access Level: | acceso abierto |
| Palabra clave: | Virtual Physiological Human Human cardiac atlas Spatio-temporal shape model Personalized cardiac EP simulation Image registration Multi-material meshing Shape modeling Predictive modeling Atlas del corazón humano Modelo espacio-temporal de forma Simulación personalizada de EF cardiaca Corregistro de imágenes Mallado de multi-materiales Modelación de formas Modelación predictiva 62 |
| Sumario: | This thesis is centered on the construction of a cardiac atlas to serve as a common reference frame in the Virtual Physiological Human (VPH). The construction covers the entire construction pipeline, starting from a set of 3D+t multislice computed tomography images, then performing a spatial normalization of these images, segmentation of the synthesized mean image, multi-structure meshing, and finally mapping of the mesh back to the population of images. In addition, two applications are presented in this thesis. First, the atlas is used to frame a spatio-temporal model of cardiac morphology which models the variability along both 'axes' simultaneously. Such a unified approach should be preferable over existing methods, which decouple the two sources of variation and then model them separately, in isolation. Second, the proposed atlas is applied to develop an acceleration technique for performing personalized simulation of cardiac electrophysiology (EP). The prior knowledge encapsulated in our atlas is used, in conjunction with a numerical solver of cardiac EP, to build a statistical model linking cardiac morphology with the steady states of myocardial cell models that pre condition detailed cardiac EP simulations. This application puts the proposed dynamic cardiac atlas in the context of VPH-related simulations, of which the computational costs are currently greatly in excess of what is acceptable for their adoption in current clinical practice. |
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