DocumentCode :
3512130
Title :
Accelerated 3D MRI of vocal tract shaping using compressed sensing and parallel imaging
Author :
Kim, Yoon-Chul ; Narayanan, Shrikanth S. ; Nayak, Krishna S.
Author_Institution :
Ming Hsieh Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA
fYear :
2009
fDate :
19-24 April 2009
Firstpage :
389
Lastpage :
392
Abstract :
3D MRI of the upper airway has provided valuable insights into vocal tract shaping and data for the modeling of speech production. Small movements of articulators can lead to large changes in the produced sound, therefore improving the resolution of these datasets, within the constraints of a sustained sound (6-12 seconds), is an important area for investigation. This paper provides the first application of compressed sensing (CS) with parallel imaging to high-resolution 3D upper airway MRI. We use spatial finite difference as the sparsifying transform, and investigate the use of high-resolution phase information as a constraint during CS reconstruction. In a retrospective subsampling experiment with no sound production, 5x undersampling produced acceptable image quality when using phase-constrained CS reconstruction. The prospective use of this accelerated acquisition enabled 3D vocal-tract MRI during sustained production of English /s/,/int/,/i/,/r/ with 1.33times1.33times1.33-mm3 spatial resolution and 10-seconds of scan time.
Keywords :
biomedical MRI; image reconstruction; image resolution; image sampling; medical image processing; 3D MRI; CS reconstruction; compressed sensing; image quality; parallel imaging; retrospective subsampling; speech production modeling; vocal tract shaping; Acceleration; Compressed sensing; Finite difference methods; High-resolution imaging; Image quality; Image reconstruction; Magnetic resonance imaging; Production; Spatial resolution; Speech; compressed sensing MRI; phase constraint; sensitivity encoding; speech production; vocal tract shaping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
ISSN :
1520-6149
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2009.4959602
Filename :
4959602
Link To Document :
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