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Abstract #1084

Self-navigated Subspace Reconstruction for Real-time MRI Speech Tracking

Peng Cao1, Wenting Jiang1, Changhe Chen2, Yiang Wang1, and Jonathan Havenhill2
1Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China, 2Department of Linguistics, The University of Hong Kong, Hong Kong, China

Synopsis

Keywords: Image Reconstruction, Motion Correction

Motivation: Real-time MRI offers a continuous and dynamic view of the object being imaged. Researchers have applied real-time MRI to speech tracking, which allows for the visualization of the vocal tract during speech production.

Goal(s): In this study, we propose applying self-navigated subspace reconstruction to real-time MRI for speech tracking.

Approach: During reconstruction, 1000 frames were compressed to a few principal components, and iterative low-rank approximation was performed on compressed k-space, greatly reducing computation costs.

Results: The proposed method allows for the joint reconstruction of all time frames and provides the dynamic motion pattern of the vocal tract at a high frame rate.

Impact: Our study presented a subspace reconstruction technique that does not require a navigator echo, which can be used for real-time MRI, particularly in speech tracking applications.

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Keywords