Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/103767
Title: Estudio de imágenes de resonancia magnética funcional en reposo para la predicción de variables personales
Author: Moral Pérez, Juan Luis
Director: Igual Muñoz, Laura
Keywords: Sistemes classificadors (Intel·ligència artificial)
Aprenentatge automàtic
Programari
Tesis
Imatges per ressonància magnètica
Learning classifier systems
Machine learning
Computer software
Theses
Magnetic resonance imaging
Issue Date: 21-Jan-2016
Abstract: This project is focused on the creation of a classification system that separates a group of subjects according to their gender based on data from magnetic resonance images (MRI) in a resting state. The images from MRI in a resting state are a tool to measure the brain connectivity or functioning that is currently being used for many neuroscience studies. This project, in particular, uses the representation of facts based on the Network in a resting state to characterize the functional connectivity of the subjects for the visualization of the obtained results. As well as evaluating the accuracy of the classification system developed, another objective of the project is to determine which of the cerebral networks are more discriminative in the task of separating men and women. The mothodology utilized combines two types of automatic learning: unsupervised learning, as in the Independent Componentes Analysis and the Principal Components Analysis, and supervised learning, as is the K-NN and SVM classifiers. The results obtained are promising, because it finds a RSN that discriminates both sex and we also note that the Principal Component Analysis does not affect when classifying .
Note: Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2016, Director: Laura Igual Muñoz
URI: http://hdl.handle.net/2445/103767
Appears in Collections:Programari - Treballs de l'alumnat
Treballs Finals de Grau (TFG) - Enginyeria Informàtica

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