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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Bibliographic Details
Published in:	Medical image analysis Vol. 72; p. 102131
Main Authors:	Woo, Jonghye, Xing, Fangxu, Prince, Jerry L., Stone, Maureen, Gomez, Arnold D., Reese, Timothy G., Wedeen, Van J., El Fakhri, Georges
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01.08.2021 Elsevier BV
Subjects:	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
Online Access:	Get full text
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