Classification Results of Artificial Neural Networks for Alzheimer’s Disease Detection

  • Alexandre Savio
  • Maite García-Sebastián
  • Carmen Hernández
  • Manuel Graña
  • Jorge Villanúa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5788)

Abstract

Detection of Alzheimer’s disease on brain Magnetic Resonance Imaging (MRI) is a highly sought goal in the Neurosciences. We used four different models of Artificial Neural Networks (ANN): Backpropagation (BP), Radial Basis Networks (RBF), Learning Vector Quantization Networks (LVQ) and Probabilistic Neural Networks (PNN) to perform classification of patients of mild Alzheimer’s disease vs. control subjects. Features are extracted from the brain volume data using Voxel-based Morphometry (VBM) detection clusters. The voxel location detection clusters given by the VBM were applied to select the voxel values upon which the classification features were computed. We have evaluated feature vectors computed from the GM segmentation volumes using the VBM clusters as voxel selection masks. The study has been performed on MRI volumes of 98 females, after careful demographic selection from the Open Access Series of Imaging Studies (OASIS) database, which is a large number of subjects compared to current reported studies.

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References

  1. 1.
  2. 2.
    Ashburner, J., Friston, K.J.: Voxel-based morphometry: The methods. Neuroimage 11(6), 805–821 (2000)CrossRefGoogle Scholar
  3. 3.
    Busatto, G.F., Garrido, G.E.J., Almeida, O.P., Castro, C.C., Camargo, C.H.P., Cid, C.G., Buchpiguel, C.A., Furuie, S., Bottino, C.M.: A voxel-based morphometry study of temporal lobe gray matter reductions in alzheimer’s disease. Neurobiology of Aging 24(2), 221–231 (2003)CrossRefGoogle Scholar
  4. 4.
    Chen, S., Cowan, C.F.N., Grant, P.M.: Orthogonal least squares learning algorithm for radial basis function networks. IEEE Transactions on Neural Networks 2(2), 302–309 (1991)CrossRefGoogle Scholar
  5. 5.
    Davatzikos, C., Fan, Y., Wu, X., Shen, D., Resnick, S.M.: Detection of prodromal alzheimer’s disease via pattern classification of magnetic resonance imaging. Neurobiology of Aging 29(4), 514–523 (2008)CrossRefGoogle Scholar
  6. 6.
    Fotenos, A.F., Snyder, A.Z., Girton, L.E., Morris, J.C., Buckner, R.L.: Normative estimates of cross-sectional and longitudinal brain volume decline in aging and AD. Neurology 64(6), 1032–1039 (2005)CrossRefGoogle Scholar
  7. 7.
    Frisoni, G.B., Testa, C., Zorzan, A., Sabattoli, F., Beltramello, A., Soininen, H., Laakso, M.P.: Detection of grey matter loss in mild alzheimer’s disease with voxel based morphometry. Journal of Neurology, Neurosurgery & Psychiatry 73(6), 657–664 (2002)CrossRefGoogle Scholar
  8. 8.
    García-Sebastián, M., Savio, A., Graña, M., Villanúa, J.: On the use of morphometry based features for Alzheimer’s disease detection on MRI. In: Omatu, S., Rocha, M.P., Bravo, J., Fernandez, F., Corchado, E., Bustillo, A., Corchado, J.M. (eds.) IWANN 2009. LNCS, vol. 5518, pp. 957–964. Springer, Heidelberg (2009)Google Scholar
  9. 9.
    Hagan, M.T., Demuth, H.B., Beale, M.H.: Neural Network Design, Har/Dsk edition. PWS Pub. Co. (December 1995)Google Scholar
  10. 10.
    Haykin, S.: Neural Networks: A Comprehensive Foundation, 2nd edn. Prentice Hall, Englewood Cliffs (1998)MATHGoogle Scholar
  11. 11.
    Huang, C., Yan, B., Jiang, H., Wang, D.: Combining voxel-based morphometry with artifical neural network theory in the application research of diagnosing alzheimer’s disease, May 2008, vol. 1, pp. 250–254 (2008)Google Scholar
  12. 12.
    Kloppel, S., Stonnington, C.M., Chu, C., Draganski, B., Scahill, R.I., Rohrer, J.D., Fox, N.C., Jack Jr., C.R., Ashburner, J., Frackowiak, R.S.J.: Automatic classification of MR scans in alzheimer’s disease. Brain 131(3), 681 (2008)CrossRefGoogle Scholar
  13. 13.
    Kohonen, T.: Self-organization and associative memory, 3rd edn. Springer-Verlag New York, Inc., New York (1989)CrossRefMATHGoogle Scholar
  14. 14.
    Lao, Z., Shen, D., Xue, Z., Karacali, B., Resnick, S.M., Davatzikos, C.: Morphological classification of brains via high-dimensional shape transformations and machine learning methods. Neuroimage 21(1), 46–57 (2004)CrossRefGoogle Scholar
  15. 15.
    Liu, Y., Teverovskiy, L., Carmichael, O., Kikinis, R., Shenton, M., Carter, C.S., Stenger, V.A., Davis, S., Aizenstein, H., Becker, J.T.: Discriminative MR image feature analysis for automatic schizophrenia and alzheimer’s disease classification. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, pp. 393–401. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  16. 16.
    Marcus, D.S., Wang, T.H., Parker, J., Csernansky, J.G., Morris, J.C., Buckner, R.L.: Open access series of imaging studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults. Journal of Cognitive Neuroscience 19(9), 1498–1507 (2007)CrossRefGoogle Scholar
  17. 17.
    Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning internal representations by error propagation, pp. 318–362. MIT Press, Cambridge (1986)Google Scholar
  18. 18.
    Scahill, R.I., Schott, J.M., Stevens, J.M., Rossor, M.N., Fox, N.C.: Mapping the evolution of regional atrophy in alzheimer’s disease: Unbiased analysis of fluid-registered serial MRI. Proceedings of the National Academy of Sciences 99(7), 4703–4707 (2002)CrossRefGoogle Scholar
  19. 19.
    Somervuo, P., Kohonen, T.: Self-Organizing maps and learning vector quantization for feature sequences. Neural Process. Lett. 10(2), 151–159 (1999)CrossRefGoogle Scholar
  20. 20.
    Specht, D.F.: Probabilistic neural networks. Neural Netw. 3(1), 109–118 (1990)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Alexandre Savio
    • 1
  • Maite García-Sebastián
    • 1
  • Carmen Hernández
    • 1
  • Manuel Graña
    • 1
  • Jorge Villanúa
    • 2
  1. 1.Grupo de Inteligencia ComputacionalSpain
  2. 2.OsatekSan SebastiánSpain

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