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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Vydáno v:	Human brain mapping Ročník 39; číslo 6; s. 2368 - 2380
Hlavní autoři:	Hu, Xintao, Huang, Heng, Peng, Bo, Han, Junwei, Liu, Nian, Lv, Jinglei, Guo, Lei, Guo, Christine, Liu, Tianming
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States John Wiley & Sons, Inc 01.06.2018 John Wiley and Sons Inc
Témata:	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
On-line přístup:	Získat plný text
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