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3 April 2023Quantifying velopharyngeal motion variation in speech sound production using an audio-informed dynamic MRI atlas
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Fangxu Xinghttps://orcid.org/0000-0002-0517-0952,1,2 Riwei Jin,3 Imani Gilbert,4 Georges El Fakhri,1 Jamie Perry,4 Bradley Sutton,3 Jonghye Woohttps://orcid.org/0000-0002-5621-92181

1Harvard Medical School (United States)
2Massachusetts General Hospital (United States)
3Univ. of Illinois (United States)
4East Carolina Univ. (United States)
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Conference Poster
Abstract
We propose a method that computes subtle motion variation patterns as principal components of a subject group’s dynamic motion fields. Coupled with the real-time speech audio recordings during image acquisition, the key time frames that contain maximum speech variations are identified by the principal components of temporally aligned audio waveforms, which in turn inform the temporal location of the maximum spatial deformation variation. Henceforth, the motion fields between the key frames and the reference frame for each subject are computed and warped into the common atlas space, enabling a direct extraction of motion variation patterns via quantitative analysis.
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Fangxu Xing,Riwei Jin,Imani Gilbert,Georges El Fakhri,Jamie Perry,Bradley Sutton, andJonghye Woo"Quantifying velopharyngeal motion variation in speech sound production using an audio-informed dynamic MRI atlas", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124642M (3 April 2023);https://doi.org/10.1117/12.2654082
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KEYWORDS
Magnetic resonance imaging
Deformation
Principal component analysis
Data acquisition
Tongue
Visualization
Laser induced plasma spectroscopy
Motion analysis
Quantitative analysis
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Fangxu Xing, Riwei Jin, Imani Gilbert, Georges El Fakhri, Jamie Perry, Bradley Sutton, Jonghye Woo, "Quantifying velopharyngeal motion variation in speech sound production using an audio-informed dynamic MRI atlas," Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124642M (3 April 2023); https://doi.org/10.1117/12.2654082
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