Detección y reconocimiento de activación en datos 4D de resonancia magnética funcional por análisis multiresolución y multivariable
In this thesis, we analyze functional magnetic resonance imaging fMRI and discusses some existing techniques to identify brain activity. We propose a methodology based on multivariate techniques: Principal Component Analysis (PCA) and Independent Component Analysis (ICA) in conjunction with wavelet...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2010 |
| País: | México |
| Institución: | Instituto Nacional de Astrofísica, Óptica y Electrónica |
| Repositorio: | Repositorio Institucional del INAOE |
| Idioma: | español |
| OAI Identifier: | oai:inaoe.repositorioinstitucional.mx:1009/542 |
| Acceso en línea: | http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/542 |
| Access Level: | acceso abierto |
| Palabra clave: | info:eu-repo/classification/Transformada de Wavelet/Wavelet transform info:eu-repo/classification/Transformada discreta de Wavelet/Discrete wavelet transform info:eu-repo/classification/Biomedical MRI/Biomedical MRI info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/22 info:eu-repo/classification/cti/2203 |
| Sumario: | In this thesis, we analyze functional magnetic resonance imaging fMRI and discusses some existing techniques to identify brain activity. We propose a methodology based on multivariate techniques: Principal Component Analysis (PCA) and Independent Component Analysis (ICA) in conjunction with wavelet decomposition, to identify brain areas involved in mental processes and perform classification of images based on the hemodynamic response. For the classification task, three known classifiers are tested: Mahalanobis, k-NN and Support Vector Machines. We report results of the proposed methodology applied to fMRI data obtained from the public repository of the fMRI Data Center. A MATLAB-based virtual instrument, which incorporates the developed algorithms, as well as utilities for fMRI images study, was developed as part of this thesis, and it is also described in this report. |
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