Identifying Early Mild Cognitive Impairment by Multi-Modality MRI-Based Deep Learning.

ABSTRACT: Mild cognitive impairment (MCI) is a clinical state with a high risk of conversion to Alzheimer's Disease (AD). Since there is no effective treatment for AD, it is extremely important to diagnose MCI as early as possible, as this makes it possible to delay its progression toward AD. However, it's challenging to identify early MCI (EMCI) because there are only mild changes in the brain structures of patients compared with a normal control (NC). To extract remarkable features for these mild changes, in this paper, a multi-modality diagnosis approach based on deep learning is presented. Firstly, we propose to use structure MRI and diffusion tensor imaging (DTI) images as the multi-modality data to identify EMCI. Then, a convolutional neural network based on transfer learning technique is deve

SUBMITTER: Kang L 

PROVIDER: S-EPMC7498722 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature