Characterizing laryngeal dynamics during voicing and breathing with real-time multi-slice variational manifold learning

Motivation: Visualizing the movement of laryngeal muscles during voicing and breathing is important for understanding the mechanics of speech production. Goal(s): The goal is to improve our understanding of speech production by visualizing gross-vocal fold movements due to laryngeal muscle contractions. Approach: We proposed a multi-slice non-gated spiral sparse sampling strategy, and variational manifold based reconstruction scheme for dynamic laryngeal MR imaging at high spatio-temporal resolution. Results: Our proposed method can capture gross vocal fold motions (e.g., adduction, abduction, elongation, shortening) during various voicing and breathing at both high spatial (1.5 mm2) and high temporal resolutions (36 ms/frame). Impact: Otolaryngologists, voice and neuroscientists interested in larynx physiology and disorders pertaining to breathing and phonation.