Multi-atlas segmentation and analysis of the fetal brain in ventriculomegaly
Nowadays, imaging of the human brain is vastly used in clinical settings and by the neuroscientific research community. There is an ever-increasing demand for novel biomedical image analysis approaches and tools to study the brain from its early intrauterine stage through adolescence to adulthood. T...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/663747 |
| Acceso en línea: | http://hdl.handle.net/10803/663747 |
| Access Level: | acceso abierto |
| Palabra clave: | Fetal brain MRI Multi-atlas segmentation Label fusion Ventriculomegaly Cortical folding MRI del cerebro fetal Segmentación multi-atlas Fusión de labels Ventriculomegalia Pliegues cerebrales 62 |
| Sumario: | Nowadays, imaging of the human brain is vastly used in clinical settings and by the neuroscientific research community. There is an ever-increasing demand for novel biomedical image analysis approaches and tools to study the brain from its early intrauterine stage through adolescence to adulthood. The intrauterine period, in particular, is a crucial stage for the study of early neurodevelopmental processes. The idiosyncratic nature of the fetal brain poses numerous challenges and asks for the development of new techniques that take into consideration the peculiarities of in utero neurodevelopment. Although still in its infancy, medical image analysis techniques are progressively landing on the study of fetal brains. The purpose of this thesis is to develop automatic segmentation approaches that can be applied to brains at different life stages, including the gestational period, and investigate in utero brain development under ventriculomegaly. |
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