title: Robust contour tracking in ultrasound tongue image sequences.
abstract: A new contour-tracking algorithm is presented for ultrasound tongue image sequences, which can follow the motion of tongue contours over long durations with good robustness. To cope with missing segments caused by noise, or by the tongue midsagittal surface being parallel to the direction of ultrasound wave propagation, active contours with a contour-similarity constraint are introduced, which can be used to provide 'prior' shape information. Also, in order to address accumulation of tracking errors over long sequences, we present an automatic re-initialization technique, based on the complex wavelet image similarity index. Experiments on synthetic data and on real 60 frame per second (fps) data from different subjects demonstrate that the proposed method gives good contour tracking for ultrasound image sequences even over durations of minutes, which can be useful in applications such as speech recognition where very long sequences must be analyzed in their entirety.
authors.affiliation: a Faculty of Engineering , Université Pierre et Marie Curie , Paris , France.|b Signal Processing and Machine Learning (SIGMA) Lab , ESPCI ParisTech , Paris , France.
authors.forename: Kele
authors.initials: K
authors.lastname: Xu
authors.affiliation: c Electrical and Computer Engineering Department , University of New Mexico , Albuquerque , New Mexico , USA.
authors.forename: Yin
authors.initials: Y
authors.lastname: Yang
authors.affiliation: d Vocal Tract Visualization Lab , University of Maryland Dental School , Baltimore , Maryland, USA.
authors.forename: Maureen
authors.initials: M
authors.lastname: Stone
authors.affiliation: a Faculty of Engineering , Université Pierre et Marie Curie , Paris , France.|b Signal Processing and Machine Learning (SIGMA) Lab , ESPCI ParisTech , Paris , France.
authors.forename: Aurore
authors.initials: A
authors.lastname: Jaumard-Hakoun
authors.affiliation: a Faculty of Engineering , Université Pierre et Marie Curie , Paris , France.|b Signal Processing and Machine Learning (SIGMA) Lab , ESPCI ParisTech , Paris , France.
authors.forename: Clémence
authors.initials: C
authors.lastname: Leboullenger
authors.affiliation: b Signal Processing and Machine Learning (SIGMA) Lab , ESPCI ParisTech , Paris , France.
authors.forename: Gérard
authors.initials: G
authors.lastname: Dreyfus
authors.affiliation: b Signal Processing and Machine Learning (SIGMA) Lab , ESPCI ParisTech , Paris , France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Roussel
authors.affiliation: e Cognitive Computing and Applications Lab , Tianjin University , Tianjin , China.
authors.forename: Bruce
authors.initials: B
authors.lastname: Denby
mesh_terms: D000465:Algorithms; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D014059:Tongue / Q000000981:diagnostic imaging / Q000502:physiology*; D014463:Ultrasonography
keywords: Active contour model; automatic re-initialization; contour tracking; similarity constraint; tongue