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LVQ-SVM based CAD tool applied to structural MRI for the diagnosis of the Alzheimer’s disease

LVQ-SVM based CAD tool applied to structural MRI for the diagnosis of the Alzheimer’s disease. Presenter : CHANG, SHIH-JIE Authors : Andrés Ortiz , Juan M. Górriz , Javier Ramírez , F.J. Martínez -Murcia 2013.PRL. Outlines. Motivation Objectives

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LVQ-SVM based CAD tool applied to structural MRI for the diagnosis of the Alzheimer’s disease

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  1. LVQ-SVM based CAD tool applied to structural MRI for the diagnosis of the Alzheimer’s disease Presenter : CHANG, SHIH-JIE Authors : Andrés Ortiz , Juan M. Górriz , Javier Ramírez , F.J. Martínez-Murcia 2013.PRL

  2. Outlines • Motivation • Objectives • Methodology • Experiments • Conclusions • Comments

  3. Motivation  The Alzheimer’s disease is at an advanced stage and there is no a known cure for the AD disease since currently .

  4. Objectives • In order to deal with objective diagnosis of the AD, this paper use many techniques to diagnosis more effective better than before.

  5. Methodology- ADNI DB(25Normal、25AD)     

  6. Methodology -Segmentation Feature extraction segmentation process : two stages 1. Classification 2. SOM Clustering CONN linkage for SOM clustering

  7. Methodology

  8. Methodology Use LVQ3 algorithm: Length w=

  9. Methodology feature reduction :    Feature generation, computed reduced features

  10. Methodology

  11. Methodology - SVM Radial Basis Function Function h:

  12. Experiments

  13. Experiments – Classification results

  14. Experiments

  15. Experiments

  16. Conclusions • The results provided by the presented method outperform other previous approaches based on MRI images. .

  17. Comments • Advantages • Good classification • Applications • Diagnosis Alzheimer’s disease

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