Abstract #0874

Spatiotemporal-atlas-based High-resolution Dynamic Speech MRI

Maojing Fu¹, Jonghye Woo², Marissa Barlaz³, Ryan Shosted³, Zhi-Pei Liang¹, and Bradley Sutton⁴

¹Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ²CAMIS (Center for Advanced Medical Imaging Sciences), Massachusetts General Hospital, Boston, MA, United States, ³Linguistics, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁴Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States

Dynamic speech MRI holds great promise for visualizing articulatory motion in the vocal tract. Recent work has enabled accelerated imaging speed, resulting in the need to integrate mechanisms to enable interpretation of the dynamic images that contain great amounts of movement information. This work integrates a spatiotemporal atlas into a partial separable (PS) model-based imaging framework and uses the atlas as prior information to improve reconstruction quality. This method not only captures high-quality dynamics at 102 frames per second, but also enables quantitative characterization of articulatory variability utilizing the residual component from the atlas-based sparsity constraint.

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