Fig 1.
Proposed system methodology.
Fig 2.
Schematic of 2D fast DWT.
Table 1.
Common kernel functions for LS-SVM.
Fig 3.
Sample images of various diseases in brain MRI dataset: (a) Normal brain (b) Glioma (c) Sarcoma (d) Alzheimer’s disease (e) Alzheimer’s disease with visual agnosia (f) Pick’s disease (g) Huntington’s disease (h) Meningioma (i) Chronic subdurnal hematoma (j) Multiple sclerosis (k) Cerebral toxoplasmosis (l) Herpes encephalitis (m) Metastatic bronchogenic carcinoma (n) Metastatic adenocarcinoma (o) Motor neuron disease (p) Cerebral calcinosis (q) AIDS dementia (r) Lyme encephalopathy (s) Creutzfeld-Jakob disease (t) Hypertensive encephalopathy (u) Multiple embolic infarctions (v) Cerebral haemorrhage (w) Cavernous angioma (x) Vascular dementia (y) fatal stroke.
Table 2.
Demographic information.
Table 3.
Settings of training and validation images for dataset groups (one pass of 5-fold stratified cross validation).
Fig 4.
Sensitivity, specificity, and accuracy with respect to the number of principal components used.
Fig 5.
ROC curves of performance evaluation: (a) Group-1 and (b) Group-2.
Table 4.
Confusion matrix of the proposed system.
Table 5.
Performance comparison using two different dataset groups.
Fig 6.
Time analysis comparison.