This project will visualize 3D tongue surface movement during speech from ultrasound, MRI and EPG data. In addition, it will use simple statistical quantities to represent important underlying patterns of tongue behavior during speech. The results will provide normative data for comparison with hearing impaired and other patient populations. Three projects will be executed. The first will reconstruct the movement of 3D tongue surfaces (4D) during speech. We can already reconstruct 3D static surfaces from 2D ultrasound slices. The proposed experiment will develop a time-alignment algorithm, which is the missing piece needed to reconstruct tongue surface movement. These will be the first- ever 4D reconstructions of the tongue. The value of such data is twofold. First, visualization of complex speech movement patterns will allow us to identify and quantify underlying patterns of movement and shape. Second, the images will be useful clinically for comparing normal and disordered patterns, and estimating the underlying musculature. The second project, which is related to the first, will quantify biologically important vocal tract and tongue surface features. The feature extraction will be done using raw ultrasound and MRI data, and also using the 3D and 4D reconstructions. The project will use statistical methods such as augmented principal components analysis, which reduce the dimensionality of a behavior. This will be particularly useful in determining group and individual subject behavior patterns, and removing noise. The components determined for normal groups and individuals can then be used for comparisons to patients. In order to do the first two objectives better, the third project will develop a family of tongue models. The models will use two very different approaches. A biokinematic model will be developed which incorporates the muscular composition of the tongue and reflects the underlying physiology. This will fill gaps in the data when reconstructing the 4D behaviors. The model will be complex enough to optimize its application to the reconstructions, but does not otherwise seek to be a perfect representation of the tongue. The second model will be a parametric statistical model which represents the complexity of 3D tongue behaviors in a simpler way. The two models are expected to converge. For example, principal components of tongue shape, though based on purely mathematical principals, should be explainable by a simplified combination of muscles, and patient deviations should be explainable by some other combination of muscles. Similarly, the biokinematic model should produce tongue surfaces that match the real data and are consistent with the statistical parameters. The biokinematic model also would benefit if the data were statistically manipulated first to reduce noise.

Agency
National Institute of Health (NIH)
Institute
National Institute on Deafness and Other Communication Disorders (NIDCD)
Type
Research Project (R01)
Project #
5R01DC001758-07
Application #
6030181
Study Section
Sensory Disorders and Language Study Section (CMS)
Project Start
1993-07-01
Project End
2001-06-30
Budget Start
1999-07-01
Budget End
2000-06-30
Support Year
7
Fiscal Year
1999
Total Cost
Indirect Cost
Name
University of Maryland Baltimore
Department
Microbiology/Immun/Virology
Type
Schools of Dentistry
DUNS #
003255213
City
Baltimore
State
MD
Country
United States
Zip Code
21201
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Parthasarathy, Vijay; Prince, Jerry L; Stone, Maureen et al. (2007) Measuring tongue motion from tagged cine-MRI using harmonic phase (HARP) processing. J Acoust Soc Am 121:491-504
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Li, Min; Kambhamettu, Chandra; Stone, Maureen (2005) Tongue motion averaging from contour sequences. Clin Linguist Phon 19:515-28
Li, Min; Kambhamettu, Chandra; Stone, Maureen (2005) Automatic contour tracking in ultrasound images. Clin Linguist Phon 19:545-54
Stone, Maureen (2005) A guide to analysing tongue motion from ultrasound images. Clin Linguist Phon 19:455-501
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Epstein, Melissa A; Stone, Maureen (2005) The tongue stops here: ultrasound imaging of the palate (L). J Acoust Soc Am 118:2128-31
NessAiver, Moriel; Prince, Jerry L (2003) Magnitude image CSPAMM reconstruction (MICSR). Magn Reson Med 50:331-42

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