Abstract：Objective The aim of this study is to research the MR images 3D texture features of corpus callosum from the patients
with mild cognitive impairment (MCI), and using the features to identify MCI and normal control (NC). Methods 3D texture
analysis was performed on 20 MCI patients and 20 NC. The three-dimensional texture features were extracted from corpus callosum
by gray-level co-occurrence matrix and run length matrix. The texture features that existed significant differences between MCI
and NC were used as the features in a classification procedure. Back propagation (BP) neural network model were built to classify
MCI patients from NC. Results The classification accuracy of the training set and test set was separately 95.83% and 93.75%.
Conclusion The back propagation neural network model with three-dimensional texture features can recognize MCI patients and NC.
张星月a，刘卫芳b. 轻度认知障碍及健康对照的分类研究[J]. 中国医疗设备, 2017, 32(10): 76-79.
ZHANG Xingyuea, LIU Weifangb. Classification Studies in Patients with Mild Cognitive Impairment and Normal Control. China Medical Devices, 2017, 32(10): 76-79.
