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A Knowledge-Based System for the Diagnosis of Alzheimer’s Disease

  • Sebastian Oehm
  • Thomas Siessmeier
  • Hans-Georg Buchholz
  • Peter Bartenstein
  • Thomas Uthmann
Conference paper
  • 452 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2780)

Abstract

Therapies to slow down the progression of Alzheimer’s disease are most effective when applied in its initial stages. Therefore it is important to develop methods to diagnose the disease as early as possible. It is also desirable to establish standards which can be used generally by physicians who may not be experts in diagnosis of the disease. One possible method to obtain an early diagnosis is the evaluation of the glucose metabolism of the brain. In this paper we present a prototype of an expert system that automatically diagnoses Alzheimer’s disease on the basis of positron emission tomography images displaying the metabolic activity in the brain.

Keywords

Positron Emission Tomography Positron Emission Tomography Image Parietal Cortex Primary Sensorimotor Cortex Average Metabolic Activity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Behl, C., Sagara, Y.: Mechanism of amyloid beta protein induced neuronal cell death: current concepts and future perspectives. J. Neural. Transm. Suppl. 49, 125–134 (1997)Google Scholar
  2. 2.
    Burdette, J.H., Minoshima, S., Borght, T.V., Tran, D.D., Kuhl, D.E.: Alzheimer disease: improved visual interpretation of PET images by using three-dimensional stereotaxic surface projections. Radiology 198, 837–843 (1996)Google Scholar
  3. 3.
    Heiss, W.D., Szelies, B., Kessler, J., Herholz, K.: Abnormalities of energy metabolism in Alzheimer’s disease studies with PET. Ann. N. Y. Acad. Sci. 640, 65–71 (1991)Google Scholar
  4. 4.
    Holman, B.L., Devous, M.D.: Functional brain SPECT: the emergence of a powerful clinical method. J. Nucl. Med. 33, 1888–1904 (1992)Google Scholar
  5. 5.
    Mayeux, R., Sano, M.: Drug therapy: treatment of Alzheimer’s disease. N. Engl. J. Med. 341, 1670–1679 (1999)CrossRefGoogle Scholar
  6. 6.
    McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., Stadlan, E.M.: Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 34, 939–944 (1984)Google Scholar
  7. 7.
    Minoshima, S., Frey, K.A., Koeppe, R.A., Foster, N.L., Kuhl, D.E.: A diagnostic approach in Alzheimer’s disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J. Nucl. Med. 36, 1238–1248 (1995)Google Scholar
  8. 8.
    Minoshima, S., Giordani, B., Berent, S., Frey, K.A., Foster, N.L., Kuhl, D.E.: Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease. Ann. Neurol. 42, 85–94 (1997)CrossRefGoogle Scholar
  9. 9.
    Oehm, S.: Entwurf und Implementation eines wissensbasierten Systems zur Diagnose der Alzheimer-Demenz. Diploma Thesis (unpublished), Dep. of Mathematics and Computer Science, Johannes Gutenberg University, Mainz, Germany (2002)Google Scholar
  10. 10.
    Talairach, J., Tournoux, P.: Co-Planar Stereotaxic Atlas of the Human Brain. Thieme Medical Publishers, New York (1988)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Sebastian Oehm
    • 1
  • Thomas Siessmeier
    • 2
  • Hans-Georg Buchholz
    • 2
  • Peter Bartenstein
    • 2
  • Thomas Uthmann
    • 1
  1. 1.Dep. of Mathematics and Computer ScienceJohannes Gutenberg UniversityMainzGermany
  2. 2.Dep. of Nuclear MedicineJohannes Gutenberg UniversityMainzGermany

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