'Indiana University Center for Genomics and Bioinformatics (CGB)'
Abstract
Data mining in brain imaging is an emerging field of high importance for providing prognosis, treatment, and a deeper understanding of how the brain functions. Dementia due to Alzheimer’s disease constitutes the fourth most common disorder among the elderly. Early detection of dementia and correct staging of the severity of dementia is critical to select the optional treatment. The present study was designed to classify and categorize brain images of dementia patients into three distinct classes ie, Normal, Moderately diseased, and Severe. Decision Forest Classifier was employed to classify the various Magnetic Resonance Images (MRIs) of dementia patients. Results of screening the MRIs are organized by classification and finally grouped into the three categories, ie, Normal, Moderate and Severe. Experimental results obtained indicated that the proposed method performs relatively well with the classification accuracy reaching nearly 99.32% in comparison with the already existing algorithms
