Left atrial parameterisation and multi-modal data analysis: application to atrial fibrillation
Many aspects related to the pathogenesis and progression of atrial fibrillation (AF) are still not fully understood. In this thesis we have contributed with (1) an automatic framework to segment the left atrium (LA) from late gadolinium enhancement magnetic resonance imaging (LGE-MRI) data, (2) a fr...
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| Tipo de documento: | tese |
| Estado: | Versão publicada |
| Data de publicação: | 2018 |
| País: | España |
| Recursos: | CBUC, CESCA |
| Repositório: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/664138 |
| Acesso em linha: | http://hdl.handle.net/10803/664138 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Left atrial parameterisation Atrial fibrillation Conformal flattening Late gadolinium enhancement MRI Atrial ablation 62 |
| Resumo: | Many aspects related to the pathogenesis and progression of atrial fibrillation (AF) are still not fully understood. In this thesis we have contributed with (1) an automatic framework to segment the left atrium (LA) from late gadolinium enhancement magnetic resonance imaging (LGE-MRI) data, (2) a framework for obtaining a standardised two-dimensional representation of the left atrial cavity, and (3) a methodology to detect and measure the incompleteness of ablation lesions after pulmonary vein isolation (PVI). Finally, we applied our tools to real clinical datasets showing how our methods can be transferred and included into clinical research practice. We investigated the regional distribution of gaps in a cohort of AF patients who undergone radiofrequency PVI, the reproducibility of scar imaging with LGE-MRI, the intra- and inter-observer variability of manual LA segmentation tools, the preferential regional distribution of fibrosis in AF patients, and the relation between electroanatomical information and LGE-MRI data. |
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