4D magnetic resonance imaging atlas construction using temporally aligned audio waveforms in speech
| Autor: | Jamie L. Perry, Fangxu Xing, Riwei Jin, Xiaofeng Liu, Jonghye Woo, Bradley P. Sutton, Ryan K. Shosted, Imani R. Gilbert, Georges El Fakhri |
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| Rok vydání: | 2021 |
| Předmět: |
Speech Communication
Similarity (geometry) Acoustics and Ultrasonics Mean squared error Cross-correlation Atlas (topology) business.industry Computer science Movement Pattern recognition Mutual information Magnetic Resonance Imaging Motion capture Motion Arts and Humanities (miscellaneous) Humans Speech Artificial intelligence business Algorithms Vocal tract Interpolation |
| Zdroj: | J Acoust Soc Am |
| ISSN: | 0001-4966 |
| DOI: | 10.1121/10.0007064 |
| Popis: | Magnetic resonance (MR) imaging is becoming an established tool in capturing articulatory and physiological motion of the structures and muscles throughout the vocal tract and enabling visual and quantitative assessment of real-time speech activities. Although motion capture speed has been regularly improved by the continual developments in high-speed MR technology, quantitative analysis of multi-subject group data remains challenging due to variations in speaking rate and imaging time among different subjects. In this paper, a workflow of post-processing methods that matches different MR image datasets within a study group is proposed. Each subject's recorded audio waveform during speech is used to extract temporal domain information and generate temporal alignment mappings from their matching pattern. The corresponding image data are resampled by deformable registration and interpolation of the deformation fields, achieving inter-subject temporal alignment between image sequences. A four-dimensional dynamic MR speech atlas is constructed using aligned volumes from four human subjects. Similarity tests between subject and target domains using the squared error, cross correlation, and mutual information measures all show an overall score increase after spatiotemporal alignment. The amount of image variability in atlas construction is reduced, indicating a quality increase in the multi-subject data for groupwise quantitative analysis. |
| Databáze: | OpenAIRE |
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