fMRI Classification Method with Multiple Feature Fusion Based on Minimum Spanning Tree Analysis

The human brain is a complex system with a sophisticated structure. As a non-invasive way to measure spontaneous neural activity in the human brain, resting-state functional magnetic resonance imaging has attracted considerable attention (Fox et al., 2007; Wang et al., 2010). Resting-state fMRI using blood oxygenation level dependent (BOLD) signals as neurophysiological indicators can detect spontaneous low-frequency brain activity and has been successfully applied to the diagnosis of neuropsychiatric diseases such as epilepsy (Horstmann et al., 2010; Raj et al., 2010), Alzheimer's disease (AD) (He et al., 2008; Stam, 2010; Supekar et al., 2008), schizophrenia (Lynall et al., 2010; Micheloyannis et al., 2006; Rubinov et al., 2009), and so on.
Source: Psychiatry Research: Neuroimaging - Category: Psychiatry Authors: Source Type: research