High spatiotemporal cineMRI films using compressed sensing for acquiring articulatory data

Benjamin Elie 1, 2 Yves Laprie 1 Pierre-André Vuissoz 2 Freddy Odille 2
1 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : The paper presents a method to acquire articulatory data from a sequence of MRI images at a high framerate. The acquisition rate is enhanced by partially collecting data in the kt-space. The combination of compressed sensing technique, along with homodyne reconstruction, enables the missing data to be recovered. The good reconstruction is guaranteed by an appropriate design of the sampling pattern. It is based on a pseudo-random Cartesian scheme, where each line is partially acquired for use of the homodyne reconstruction, and where the lines are pseudo-randomly sampled: central lines are constantly acquired and the sampling density decreases as the lines are far from the center. Application on real speech data show that the framework enables dynamic sequences of vocal tract images to be recovered at a framerate higher than 30 frames per second and with a spatial resolution of 1 mm. A method to extract articulatory data from contour identification is presented. It is intended, in fine, to be used for the creation of a large database of articulatory data.
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Benjamin Elie, Yves Laprie, Pierre-André Vuissoz, Freddy Odille. High spatiotemporal cineMRI films using compressed sensing for acquiring articulatory data. EUSIPCO2016, Aug 2016, Budapest, Hungary. ⟨hal-01372320⟩

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