A deep joint sparse non-negative matrix factorization framework for identifying the common and subject-specific functional units of tongue motion during speech

•We presented a method to identify both common and subject-specific functional units within a material coordinate system from MRI.•We proposed to convert non-negative matrix factorization with sparse and manifold regularizations into modular structures.•We provided validation to demonstrate superior...

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Vydáno v:	Medical image analysis Ročník 72; s. 102131
Hlavní autoři:	Woo, Jonghye, Xing, Fangxu, Prince, Jerry L., Stone, Maureen, Gomez, Arnold D., Reese, Timothy G., Wedeen, Van J., El Fakhri, Georges
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Netherlands Elsevier B.V 01.08.2021 Elsevier BV
Témata:	Algorithms Artificial neural networks Clustering Coordination Coordination compounds Deep learning Deep non-negative matrix factorization Factorization Functional units Humans In vivo methods and tests Joints (anatomy) Machine learning Magnetic Resonance Imaging Muscles Neural networks Neural Networks, Computer Speech Structure-function relationships Tagged-MRI Tongue Tongue - diagnostic imaging Tongue motion Weighting Tagged-MRI Functional units Deep non-negative matrix factorization Tongue motion
ISSN:	1361-8415, 1361-8423, 1361-8423
On-line přístup:	Získat plný text
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