Back to Search Start Over

High spatiotemporal cineMRI films using compressed sensing for acquiring articulatory data

Authors :
Pierre-André Vuissoz
Yves Laprie
Benjamin Elie
Freddy Odille
Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH)
Inria Nancy - Grand Est
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD)
Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)
Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)
Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)
Imagerie Adaptative Diagnostique et Interventionnelle (IADI)
Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)
FEDER et Région Lorraine
Elie, Benjamin
Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)
Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Source :
EUSIPCO, 24th European Signal Processing Conference-EUSIPCO2016, 24th European Signal Processing Conference-EUSIPCO2016, Aug 2016, Budapest, Hungary. ⟨10.1109/EUSIPCO.2016.7760469⟩, 2016 24th European Signal Processing Conference (EUSIPCO), 2016 24th European Signal Processing Conference (EUSIPCO), Aug 2016, Budapest, France. pp.1353-1357, ⟨10.1109/EUSIPCO.2016.7760469⟩
Publication Year :
2016
Publisher :
IEEE, 2016.

Abstract

International audience; 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.

Details

Database :
OpenAIRE
Journal :
2016 24th European Signal Processing Conference (EUSIPCO)
Accession number :
edsair.doi.dedup.....a1db56b3e7c1fa43e852cb6777a6b206
Full Text :
https://doi.org/10.1109/eusipco.2016.7760469