Brain Disease Classification & Brain Age Estimation Using CNN

Here, brain disease classification and brain age are estimated using convolutional neural networks. Brain morphometric pattern analysis has been increasingly investigated to identify age-related imaging biomarkers from structural magnetic resonance imaging (MRI). 

Compared with other biomedical image modalities, MRI is a non-invasive means of potentially identifying abnormal structural brain changes in a more sensitive manner. Abnormality/normality like Mild Cognitive Impairment (MCI), Alzheimer's Disease (AD), and Healthy Control (HC) were classified using brain MRI images. 

Accuracy of traditional method, Support Vector Machine (SVM) is analyzed, implemented, and compared with the novel Convolutional Neural Network (CNN) which is of deep learning technique. After these processes, the range of brain age is estimated which is based on type of abnormality/normality.

Keywords: Convolutional neural network, Deep learning, Support vector machine, Magnetic resonance imaging.