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

Perez de Alejo, Rigoberto and Ruiz Cabello Osuna, Jesus Maria and Cortijo Martinez, Manuel and Rodriguez, Ignacio and Echave, Imanuel and Regadera, Javier and Arrazola, Juan and Aviles, Pablo and Barreiro Elorza, Pilar and Gargallo, Domingo and 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.

Description

Title: Computer assisted enhanced volumetric segmentation magnetic imaging data using a mixture of artificial neural networks
Author/s:
  • 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
Item Type: Article
Título de Revista/Publicación: Magnetic Resonance Imaging
Date: October 2003
ISSN: 0730-725X
Volume: 21
Subjects:
Faculty: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Department: Ingeniería Rural [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview

Abstract

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)

More information

Item ID: 6138
DC Identifier: http://oa.upm.es/6138/
OAI Identifier: oai:oa.upm.es:6138
DOI: 10.1016/S0730-725X(03)00193-0
Official URL: http://www.sciencedirect.com/science/journal/0730725X
Deposited by: Memoria Investigacion
Deposited on: 23 Feb 2011 10:00
Last Modified: 20 Apr 2016 15:27
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM