Computer assisted enhanced volumetric segmentation magnetic imaging data using a mixture of artificial neural networks

Perez de Alejo, Rigoberto; Ruiz Cabello Osuna, Jesus Maria; Cortijo Martinez, Manuel; Rodriguez, Ignacio; Echave, Imanuel; Regadera, Javier; Arrazola, Juan; Aviles, Pablo; Barreiro Elorza, Pilar; Gargallo, Domingo y Graña, Manuel (2003). Computer assisted enhanced volumetric segmentation magnetic imaging data using a mixture of artificial neural networks. "Magnetic Resonance Imaging", v. 21 (n. 8); pp. 901-912. ISSN 0730-725X. https://doi.org/10.1016/S0730-725X(03)00193-0.

Descripción

Título: 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, Pilar
  • Gargallo, Domingo
  • Graña, Manuel
Tipo de Documento: Artículo
Título de Revista/Publicación: Magnetic Resonance Imaging
Fecha: Octubre 2003
Volumen: 21
Materias:
Escuela: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Departamento: Ingeniería Rural [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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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 collected from an experimental acute inflammatory model (T(2) weighted) and from a clinical study of human Alzheimer's disease (T(1) weighted) to evaluate the proposed method. In the first case, a high correlation and parallelism was registered between the volumetric measurements, of the injured and healthy tissue, by the proposed method with respect to the manual measurements (r = 0.82 and p < 0.05) and to the histopathological studies (r = 0.87 and p < 0.05). The method was also applied to the clinical studies, and similar results were derived of the manual and semi-automatic volumetric measurement of both hippocampus and the corpus callosum (0.95 and 0.88)

Más información

ID de Registro: 6138
Identificador DC: http://oa.upm.es/6138/
Identificador OAI: oai:oa.upm.es:6138
Identificador DOI: 10.1016/S0730-725X(03)00193-0
URL Oficial: http://www.sciencedirect.com/science/journal/0730725X
Depositado por: Memoria Investigacion
Depositado el: 23 Feb 2011 10:00
Ultima Modificación: 20 Abr 2016 15:27
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