Detection of Alzheimer's disease and mild cognitive impairment based on structural volumetric MR images using 3D-DWT and WTA-KSVM trained by PSOTVAC

- We take the whole brain (not the ROIs) as the research objective, so there is no need for brain segmentation.
- The sensitivity of NC is up to 93.81%. The specificities of MCI and AD are 93.39% and 92.21%.
- We use 3D-DWT to capture the 3D texture feature of brain, use ALS-PCA for feature reduction of dataset containing missing attributes.
- We use TVAC-PSO to get the optimal kernel parameter of each individual KSVM.
- We compare three different multiclass KSVM methods, and find that WTA performs best.