Evaluation of Alzheimer's disease by analysis of MR images using multilayer perceptrons, polynomial nets and Kohonen LVQ classifiers

  • Authors:

  • Wellington P. dos Santos;Ricardo E. de Souza;Ascendino F. D. e Silva;Plínio B. Santos Filho

  • Affiliations:

  • Universidade Federal de Pernambuco, Departamento de Eletrônica e Sistemas, Cidade Universitária, Brazil and Universidade de Pernambuco, Departamento de Sistemas Computacionais, Madalena, ...;Universidade Federal de Pernambuco, Departamento de Fíde, Universitá, Brazil;Universidade Federal de Pernambuco, Departamento de Eletrônica e Sistemas, Cidade Universitária, Brazil;North Carolina State University,Department of Physics

  • Venue:
  • MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
  • Year:
  • 2007

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Abstract

Alzheimer's disease is the most common cause of dementia, yet hard to diagnose precisely without invasive techniques, particularly at the onset of the disease. This work approaches image analysis and classification of synthetic multispectral images composed by diffusion-weighted magnetic resonance (MR) cerebral images for the evaluation of cerebrospinal fluid area and its correlation with the advance of Alzheimer's disease. The MR images were acquired from an image system by a clinical 1.5 T tomographer. The classification methods are based on multilayer perceptrons, polynomial nets and Kohonen LVQ classifiers. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map.