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

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.