Latent source mining in FMRI via restricted Boltzmann machine

Blind source separation (BSS) is commonly used in functional magnetic resonance imaging (fMRI) data analysis. Recently, BSS models based on restricted Boltzmann machine (RBM), one of the building blocks of deep learning models, have been shown to improve brain network identification compared to conv...

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Bibliographic Details
Published in:	Human brain mapping Vol. 39; no. 6; pp. 2368 - 2380
Main Authors:	Hu, Xintao, Huang, Heng, Peng, Bo, Han, Junwei, Liu, Nian, Lv, Jinglei, Guo, Lei, Guo, Christine, Liu, Tianming
Format:	Journal Article
Language:	English
Published:	United States John Wiley & Sons, Inc 01.06.2018 John Wiley and Sons Inc
Subjects:	Algorithms blind source separation Brain Brain - diagnostic imaging Brain Mapping Complexity Data analysis Data mining Data processing Datasets as Topic - statistics & numerical data Functional magnetic resonance imaging Humans Image Processing, Computer-Assisted Independent component analysis Machine learning Magnetic Resonance Imaging Models, Neurological Neuroimaging Oxygen - blood restricted Boltzmann machine Signal processing Task Performance and Analysis Training blind source separation functional magnetic resonance imaging restricted Boltzmann machine
ISSN:	1065-9471, 1097-0193, 1097-0193
Online Access:	Get full text
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