title: High-resolution dynamic speech imaging with joint low-rank and sparsity constraints.
abstract: OBJECTIVE
  To enable dynamic speech imaging with high spatiotemporal resolution and full-vocal-tract spatial coverage, leveraging recent advances in sparse sampling.
  
  
  METHODS
  An imaging method is developed to enable high-speed dynamic speech imaging exploiting low-rank and sparsity of the dynamic images of articulatory motion during speech. The proposed method includes: (a) a novel data acquisition strategy that collects spiral navigators with high temporal frame rate and (b) an image reconstruction method that derives temporal subspaces from navigators and reconstructs high-resolution images from sparsely sampled data with joint low-rank and sparsity constraints.
  
  
  RESULTS
  The proposed method has been systematically evaluated and validated through several dynamic speech experiments. A nominal imaging speed of 102 frames per second (fps) was achieved for a single-slice imaging protocol with a spatial resolution of 2.2 × 2.2 × 6.5 mm(3) . An eight-slice imaging protocol covering the entire vocal tract achieved a nominal imaging speed of 12.8 fps with the identical spatial resolution. The effectiveness of the proposed method and its practical utility was also demonstrated in a phonetic investigation.
  
  
  CONCLUSIONS
  High spatiotemporal resolution with full-vocal-tract spatial coverage can be achieved for dynamic speech imaging experiments with low-rank and sparsity constraints.
authors.affiliation: Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA; Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
authors.forename: Maojing
authors.initials: M
authors.lastname: Fu
authors.forename: Bo
authors.initials: B
authors.lastname: Zhao
authors.forename: Christopher
authors.initials: C
authors.lastname: Carignan
authors.forename: Ryan K
authors.initials: RK
authors.lastname: Shosted
authors.forename: Jamie L
authors.initials: JL
authors.lastname: Perry
authors.forename: David P
authors.initials: DP
authors.lastname: Kuehn
authors.forename: Zhi-Pei
authors.initials: ZP
authors.lastname: Liang
authors.forename: Bradley P
authors.initials: BP
authors.lastname: Sutton
mesh_terms: D003198:Computer Simulation; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D009055:Mouth / Q000502:physiology*; D009296:Nasal Cavity / Q000502:physiology*; D010160:Palate, Soft / Q000502:physiology*; D010614:Pharynx / Q000502:physiology*; D010699:Phonation / Q000502:physiology*; D010700:Phonetics; D012016:Reference Values; D013060:Speech / Q000502:physiology*; D013061:Speech Acoustics; D013062:Speech Articulation Tests / Q000295:instrumentation / Q000379:methods*; D014059:Tongue / Q000502:physiology*
keywords: dynamic speech imaging; low-rank approximation; partial separability modeling; sparsity; spiral navigation