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Selecting Regions of Interest for the Diagnosis of Alzheimer Using Brain SPECT Images

  • Diego Salas-Gonzalez
  • Juan M. Górriz
  • Javier Ramírez
  • Ignacio Álvarez
  • Míriam López
  • Fermín Segovia
  • Carlos G. Puntonet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5553)

Abstract

This paper presents a computer-aided diagnosis technique for improving the accuracy of the early diagnosis of the Alzheimer type dementia. The proposed methodology is based on the selection of those voxels which present a greater difference between normals and Alzheimer’s type dementia patients. The mean value of the intensities of the selected voxels are used as features for different classifiers. The proposed methodology reaches an accuracy of 89% in the classification task.

Keywords

Automatic Computer Aided Diagnosis Classification SPECT imaging Alzheimer’s disease 

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References

  1. 1.
    Holman, B.L., Johnson, K.A., Gerada, B., Carvalho, P.A., Satlin, A.: The Scintigraphic Appearance of Alzheimer’s Disease: A Prospective Study Using Technetium-99m-HMPAO SPECT. Journal of Nuclear Medicine 33(2), 181–185 (1992)Google Scholar
  2. 2.
    Jagust, W., Thisted, R., Devous, M.D., Heertum, R.V., Mayberg, H., Jobst, K., Smith, A.D., Borys, N.: Spect Perfusion Imaging in the Diagnosis of Alzheimer’s Disease: A Clinical-pathologic Study. Neurology 56, 950–956 (2001)CrossRefGoogle Scholar
  3. 3.
    McNeill, R., Sare, G.M., Manoharan, M., Testa, H.J., Mann, D.M.A., Neary, D., Snowden, J.S., Varma, A.R.: Accuracy of Single-photon Emission Computed Tomography in Differentiating Frontotemporal Dementia from Alzheimer’s Disease. J. Neurol. Neurosurg. Psychiatry 78(4), 350–355 (2007)CrossRefGoogle Scholar
  4. 4.
    Ramírez, J., Górriz, J.M., Romero, A., Lassl, A., Salas-Gonzalez, D., López, M., Gómez-Río, M., Rodríguez, A.: Computer Aided Diagnosis of Alzheimer Type Dementia Combining Support Vector Machines and Discriminant Set of Features. Information Sciences (accepted) (2008)Google Scholar
  5. 5.
    Fung, G., Stoeckel, J.: SVM Feature Selection for Classification of SPECT Images of Alzheimer’s Disease Using Spatial Information. Knowledge and Information Systems 11(2), 243–258 (2007)CrossRefGoogle Scholar
  6. 6.
    Górriz, J.M., Ramírez, J., Lassl, A., Salas-Gonzalez, D., Lang, E.W., Puntonet, C.G., Álvarez, I., López, M., Gómez-Río, M.: Automatic Computer Aided Diagnosis Tool Using Component-based SVM. In: Medical Imaging Conference, Dresden. IEEE, Los Alamitos (2008)Google Scholar
  7. 7.
    Lassl, A., Górriz, J.M., Ramírez, J., Salas-Gonzalez, D., Puntonet, C.G., Lang, E.W.: Clustering Approach for the Classification of Spect Images. In: Medical Imaging Conference, Dresden. IEEE, Los Alamitos (2008)Google Scholar
  8. 8.
    Krzanowski, W.J. (ed.): Principles of Multivariate Analysis: A User’s Perspective. Oxford University Press, Inc., New York (1988)zbMATHGoogle Scholar
  9. 9.
    Ramírez, J., Górriz, J.M., Gómez-Río, M., Romero, A., Chaves, R., Lassl, A., Rodríguez, A., Puntonet, C.G., Theis, F., Lang, E.: Effective Emission Tomography Image Reconstruction Algorithms for Spect Data. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2008, Part I. LNCS, vol. 5101, pp. 741–748. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  10. 10.
    Salas-Gonzalez, D., Górriz, J.M., Ramírez, J., Lassl, A., Puntonet, C.G.: Improved Gauss-newton Optimization Methods in Affine Registration of Spect Brain Images. IET Electronics Letters 44(22), 1291–1292 (2008)CrossRefGoogle Scholar
  11. 11.
    Ashburner, J., Friston, K.J.: Nonlinear Spatial Normalization Using Basis Functions. Human Brain Mapping 7(4), 254–266 (1999)CrossRefGoogle Scholar
  12. 12.
    Saxena, P., Pavel, D.G., Quintana, J.C., Horwitz, B.: An automatic threshold-based scaling method for enhancing the usefulness of Tc-HMPAO SPECT in the diagnosis of Alzheimer’s disease. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 623–630. Springer, Heidelberg (1998)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Diego Salas-Gonzalez
    • 1
  • Juan M. Górriz
    • 1
  • Javier Ramírez
    • 1
  • Ignacio Álvarez
    • 1
  • Míriam López
    • 1
  • Fermín Segovia
    • 1
  • Carlos G. Puntonet
    • 2
  1. 1.Dept. of Signal Theory, Networking and CommunicationsUniversity of GranadaGranadaSpain
  2. 2.Dept. of Computer Architecture and Computer TechnologyUniversity of GranadaGranadaSpain

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