The invention discloses an early and late mild cognitive impairment classification method and device based on brain function network characteristics and belongs to the medical image processing technology field. According to the method, firstly, sample data is pre-processed, multiple brain region time series are extracted, the brain function network is constructed by utilizing a correlation coefficient between the Pearson's correlation calculation brain area time series, and brain network parameters are calculated; secondly, the stepwise analysis method is utilized to extract characteristics, abinary classifier is trained, corresponding characteristic vectors are extracted from to-be-classified resting state functional magnetic resonance data and are inputted to the trained binary classifier, and the medical image classification result is acquired. Compared with a method in the prior art, the method is advantaged in that classification accuracy, sensitivity and specificity are better.
Early and late mild cognitive impairment classification method and device based on brain function network characteristics