Computer assisted enhanced volumetric segmentation magnetic imaging data using a mixture of artificial neural networks
Título de la tesis:
Computer assisted enhanced volumetric segmentation magnetic imaging data using a mixture of artificial neural networks
Autor/es:
Perez de Alejo, Rigoberto - Ruiz Cabello Osuna, Jesus Maria - Cortijo Martinez, Manuel - Rodriguez, Ignacio - Echave, Imanuel - Regadera, Javier - Arrazola, Juan - Aviles, Pablo - Barreiro Elorza, Pil
Tipo de documento:
Artículo
Universidad:
E.T.S.I. Agrónomos (UPM)
Departamento:
Ingeniería Rural
Idioma:
Palabras clave:
Fecha de la defensa:
Octubre 2003-01-01
Notas:
Resumen: An accurate computer-assisted method able to perform regional segmentation on 3D single modality images and measure its volume is designed using a mixture of unsupervised and supervised artificial neural networks. Firstly, an unsupervised artificial neural network is used to estimate representative textures that appear in the images. The region of interest of the resultant images is selected by means of a multi-layer perceptron after a training using a single sample slice, which contains a central portion of the 3D region of interest. The method was applied to magnetic resonance imaging data c...
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