## 3 Application examples of CAD for brain diseases
### Alzheimer's disease  
Alzheimer's disease (AD) is an irreversible, progressive dementing disorder, which slowly deteriorates memory and thinking skills [78]. Since the incidence of the AD is strongly linked to the age, the AD is one of the major public health problems in countries with the longer life expectancy. According to recent estimates, as many as 2.4 million to 4.5 million Americans and 1.8 million Japanese have AD [78, 79]. AD is associated with the atrophy of gray matter in the cerebral cortex, which leads to a volume decrease of the cerebral cortex or a volume increase of cerebrospinal fluid (CSF) in cerebral sulci and lateral ventricles (LVs), which can be measured in magnetic resonance \begin{table}
\begin{tabular}{c c c c c} \hline Authors & \
\begin{tabular}{c} Lesion \\ enhancement \\ \end{tabular} & Classifier &
\begin{tabular}{c} No.cases \\ (No.WMHs) \\ \end{tabular} & SI* \\ \hline [PERSON] _et al._[75] & k-nearest & k-nearest & 19 (-) & 0.81 \\ [PERSON] _et al._ & Fuzzy C-mean & Fuzzy & 100 (100) & 0.75 \\
[74] & algorithm & & & \\  & FLAIR**-T1 & & & \\ [PERSON] _et al._[28] & difference & ANN*** & 9 (85) & 0.74 \\  & image & & & \\ \hline \multicolumn{4}{l}{*SI: similarity index} \\ \multicolumn{4}{l}{**FLAIR: fluid-attenuated inversion-recovery} \\ \multicolumn{4}{l}{***ANN: artificial neural network} \\ \end{tabular}
\end{table} 
Table 2: Comparison of methods and performance of CAD systems for detection of white matter hyperintensities (WMHs) in MR images. Figure 12: Illustrations of (a) an original T1-weighted image, (b) an original fluid-attenuated inversion-recovery (FLAIR) image with hyperintense regions, (c) a subtraction image between the FLAIR image and T1-weighted image [28]. (MR) images. In order to provide appropriate care for AD patients, it is very important to quantitatively evaluate the degree of the atrophy in the cerebral cortex in the early stages of AD. Neuroradiologists attempt to estimate the degree of atrophy by capturing atrophic image features on MR images, but it is very difficult and time consuming in routine clinical practice. Therefore, a number of automated methods have been studied for identification of AD patients among the large number of patients with dementia [27,80-83]. In recent years, a whole-brain unbiased objective technique, known as voxel-based morphometry (VBM) [84], has been developed for characterizing differences in the local composition of brain tissue using MR images, and can objectively map gray matter loss on a voxel-by-voxel basis. [PERSON] _et al._[80] developed a software based on the voxel-based specific region analysis for Alzheimer's disease (VSRAD), which can automatically analyze 3D T1-weighted MRI data as a series of segmentation, anatomical standardization and smoothing using a VBM software (statistical parametric mapping: SPM) and _Z_-score analysis. The averaged value of positive _Z_-scores with respect to the volumes in the specific region of interest in a _Z_-score map was as the threshold for classifying AD cases and non-AD cases. [PERSON] _et al._[81] employed a SVM for characterization of the hippocampal volume changes in AD and differentiation of AD patients from healthy control subjects. [PERSON] _et al._[82] also used linear support vector machines to classify the gray matter segment of T1-weighted MR scans from AD patients and normal elderly individuals. In their method, MR images were segmented into gray matter (GM), white matter and CSF using SPM. [PERSON] _et al._[83] developed an automated segmentation method for hippocampal volumetry to help distinguish between patients with AD, patients with mild cognitive impairment (MCI), and elderly controls, by using established criteria for patients with AD and MCI as the reference standard. Table 3 shows the comparison of methods and performances of CAD systems for Alzheimer's disease using MR images. The accuracy for classification of AD patients ranges from 82.7% to 89.6%, which seems to be relatively high accuracy.