Content based retrieval of MRI based on brain structure changes in Alzheimer’s disease

Abstract

The aim of the paper is to present Content Based Retrieval of MRI based on the brain structure changes characteristic for Alzheimer’s Disease (AD). The approach used in this paper aims to improve the retrieval performance while using smaller number of features in comparison to the descriptor dimensionality generated by the traditional feature extraction techniques. The feature vector consists of the measurements of cortical and subcortical brain structures, including volumes of the brain structures and cortical thickness. Two main stages are required to obtain these features: segmentation and calculation of the quantitative measurements. The feature subset selection is additionally applied using Correlation-based Feature Selection (CFS) method. Euclidean distance is used as a similarity measurement. The retrieval performance is evaluated using MRIs provided by the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Experimental results show that the strategy used in this research outperforms the traditional one despite its simplicity and small number of features used for representation.