Computer-aided diagnosis of Alzheimer's disease using support vector machines and classification trees.
This paper presents a computer-aided diagnosis technique for improving the accuracy of early diagnosis of Alzheimer-type dementia. The proposed methodology is based on the selection of voxels which present Welch's t-test between both classes, normal and Alzheimer images, greater than a given threshold. The mean and standard deviation of intensity values are calculated for selected voxels. They are chosen as feature vectors for two different classifiers: support vector machines with linear kernel and classification trees. The proposed methodology reaches greater than 95% accuracy in the classification task.
Salas-Gonzalez
D
D
Department of Signal Theory Networking and Communications, ETSIIT, University of Granada, Spain. dsalas@ugr.es
Górriz
J M
JM
Ramírez
J
J
López
M
M
Alvarez
I
I
Segovia
F
F
Chaves
R
R
Puntonet
C G
CG
D000544:Alzheimer Disease / Q000175:diagnosis* / Q000000981:diagnostic imaging; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D015899:Tomography, Emission-Computed, Single-Photon / Q000145:classification