Multi-Band Brain Network Analysis for Functional Neuroimaging Biomarker Identification

• Published in: IEEE transactions on medical imaging Vol. 40; no. 12; pp. 3843 - 3855
• Main Authors: Hu, Rongyao, Peng, Ziwen, Zhu, Xiaofeng, Gan, Jiangzhang, Zhu, Yonghua, Ma, Junbo, Wu, Guorong
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.12.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Alzheimer Disease - diagnostic imaging; Alzheimer's disease; Biomarkers; Biomedical imaging; Brain; Brain - diagnostic imaging; Connectivity analysis; Connectome; Correlation; Dementia disorders; Diagnosis; Diagnostic systems; Discrete Wavelet Transform; Frequencies; Frontotemporal dementia; Functional connectivity; Functional magnetic resonance imaging; High frequency; Humans; Image processing; Machine learning; Magnetic Resonance Imaging; Medical diagnosis; Medical imaging; Network analysis; Neural networks; neuro-disease diagnosis; Neurodegenerative diseases; Neuroimaging; Obsessive compulsive disorder; Oscillations; Oxygenation; resting state fMRI; semi-supervised learning; Source code; Support vector machines; Wavelet transforms

The functional connectomic profile is one of the non-invasive imaging biomarkers in the computer-assisted diagnostic system for many neuro-diseases. However, the diagnostic power of functional connectivity is challenged by mixed frequency-specific neuronal oscillations in the brain, which makes the...