METHOD FOR ESTABLISHING PREDICTION MODEL BASED ON MULTIDIMENSIONAL TEXTURE OF BRAIN NUCLEAR MAGNETIC RESONANCE IMAGES

摘要

Disclosed is a method for establishing a prediction model based on a multidimensional texture of brain nuclear magnetic resonance images. Images are segmented using a region growing method, a contourlet transform method is used to extract an edge texture feature parameter of ROIs, a multidimensional database is established, and a prediction model is established using various data mining methods, comprising a Gaussian process, a support vector machine, a random forest, a Lasso regression and a semi-supervised support vector machine. The ROIs comprise a hippocampus region and an entorhinal cortex region.