Multiview Feature Learning With Multiatlas-Based Functional Connectivity Networks for MCI Diagnosis

• Published in: IEEE transactions on cybernetics Vol. 52; no. 7; pp. 1 - 12
• Main Authors: Zhang, Yu, Zhang, Han, Adeli, Ehsan, Chen, Xiaobo, Liu, Mingxia, Shen, Dinggang
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Alzheimer's disease; Brain; Brain disease diagnosis; Diagnosis; Disease control; Diseases; Feature extraction; functional connectivity (FC); Image classification; Machine learning; Magnetic heads; Magnetic resonance imaging; Medical diagnosis; Medical imaging; mild cognitive impairment (MCI); multinetwork classification; Networks; Pathology; resting-state functional magnetic resonance imaging (rs-fMRI); Support vector machines

Functional connectivity (FC) networks built from resting-state functional magnetic resonance imaging (rs-fMRI) has shown promising results for the diagnosis of Alzheimer's disease and its prodromal stage, that is, mild cognitive impairment (MCI). FC is usually estimated as a temporal correlatio...