Traditional magnetic resonance imaging analysis methods measure the volume of region of interests (ROI), as well as the regional difference in whole brain. As the introduction of many computer vision and mathematics methods, the segmentation and registration methods are widely used and highly improved, and the surface reconstruction and shape analysis are getting more attention. This paper proposes several methods on both traditional volume counting and shape analysis. The main contributions are as follows: 1. In patients of Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI), the studies on hippocampus volume report controversial results, and few of them concerns the left-right asymmetry of hippocampus. We introduce Meta-analysis method to integrate the results. By analyzing hippocampus volume differnece in 28 papers, the combined atrophy rates are obtained in AD and MCI. The findings also show a left-less-than-right pattern, which is maximum in MCI and minimum in AD. Our results find the hippocampus is involved in AD and MCI early, and the asymmery could be a candidate biomarker besides hippocampus volume. 2. We introduce the Banana-like model in hippocampus surface reconstruction, and describe its shape with 400*200 grids. The area of ISO-circle is registered to the mean area curve and point correspondence is improved in this way. The radial distance from each vertex on surface to the mid-axis is taken as measurement. After applying to 19 Alzheimer’s Disease patients and 20 normal controls, significant atrophy is found in left hippocampus, mainly in lateral and middle regions. This findings are consistant with the volume counting results but provide more precise location of abnormal regions, which could help to study the pathology reasons of hippocampus atrophy. 3. We employ VBM method to find abnormal regions of whole brain in early blind, who may experience abnormal cortical development process caused by visual deprivation. Results show significant bilateral white matter and cuneus atrophy, but left lingual gyrus is inflated. Then, a cortex modeling method is used. The findings show early blindness have higher cortical thickness in Brodmann 17/18, but the area of that region is smaller than that of controls. This reveals the horizontal shrinking is concurrent with vertical inflation. This finding suggests the synaptic pruning and myelination process may be interrupted by lacking of visual experience during brain developing. 4. We propose a pattern classification method for combing the neuroimaging properties and clinical diagnosis. Features are first extracted from regional homogeneity attribute in time-series of fMRI. After feature selection and dimension reduction, we get the discriminative model with training images and achive 80% average correct rate in leave-one-out cross validation. This suggests the automatic patients classification based on neuroimaging measurements is feasible.
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