Attention-Guided Hybrid Network for Dementia Diagnosis With Structural MR Images.

ABSTRACT: Deep-learning methods (especially convolutional neural networks) using structural magnetic resonance imaging (sMRI) data have been successfully applied to computer-aided diagnosis (CAD) of Alzheimer's disease (AD) and its prodromal stage [i.e., mild cognitive impairment (MCI)]. As it is practically challenging to capture local and subtle disease-associated abnormalities directly from the whole-brain sMRI, most of those deep-learning approaches empirically preselect disease-associated sMRI brain regions for model construction. Considering that such isolated selection of potentially informative brain locations might be suboptimal, very few methods have been proposed to perform disease-associated discriminative region localization and disease diagnosis in a unified deep-learning framework. Ho

SUBMITTER: Lian C 

PROVIDER: S-EPMC7855081 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature