Atlas-based tongue muscle correlation analysis from tagged and high- resolution magnetic resonance imaging

Fangxu Xing, Maureen Stone, Tessa Goldsmith, Jerry L. Prince, Georges El Fakhri, Jonghye Woo

Research output: Contribution to journalArticle

Abstract

Purpose: Intrinsic and extrinsic tongue muscles in healthy and diseased populations vary both in their intra- and intersubject behaviors during speech. Identifying coordination patterns among various tongue muscles can provide insights into speech motor control and help in developing new therapeutic and rehabilitative strategies. Method: We present a method to analyze multisubject tongue muscle correlation using motion patterns in speech sound production. Motion of muscles is captured using tagged magnetic resonance imaging and computed using a phasebased deformation extraction algorithm. After being assembled in a common atlas space, motions from multiple subjects are extracted at each individual muscle location based on a manually labeled mask using high-resolution magnetic resonance imaging and a vocal tract atlas. Motion correlation between each muscle pair is computed within each labeled region. The analysis is performed on a population of 16 control subjects and 3 post–partial glossectomy patients. Results: The floor-of-mouth (FOM) muscles show reduced correlation comparing to the internal tongue muscles. Patients present a higher amount of overall correlation between all muscles and exercise en bloc movements. Conclusions: Correlation matrices in the atlas space show the coordination of tongue muscles in speech sound production. The FOM muscles are weakly correlated with the internal tongue muscles. Patients tend to use FOM muscles more than controls to compensate for their postsurgery function loss.

Original languageEnglish (US)
Pages (from-to)2258-2269
Number of pages12
JournalJournal of Speech, Language, and Hearing Research
Volume62
Issue number7
DOIs
StatePublished - Jul 2019

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Speech and Hearing

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