Segmentation of tongue shapes during vowel production in magnetic resonance images based on statistical modelling

• Type: Article in International Scientific Journal
• Date: 2018-03

Authors

Jessica C. Delmoral (Author) Other; Sandra M. Rua Ventura (Author) Other; João Manuel R. S. Tavares (Author) FEUP

Journal

Title: Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine

Vol. 232 No. 3

Pages: 271-281

ISSN: 0954-4119

Publisher: SAGE

Indexing

ISI Web of Knowledge - 0 Citations

ISI Web of Science

Scopus - 1 Citation

INSPEC

Scientific classification

CORDIS: Technological sciences

FOS: Engineering and technology

Other information

Authenticus ID: P-00N-R0A

DOI: 10.1177/0954411917751000

Abstract (EN): Quantification of the anatomic and functional aspects of the tongue is pertinent to analyse the mechanisms involved in speech production. Speech requires dynamic and complex articulation of the vocal tract organs, and the tongue is one of the main articulators during speech production. Magnetic resonance imaging has been widely used in speech-related studies. Moreover, the segmentation of such images of speech organs is required to extract reliable statistical data. However, standard solutions to analyse a large set of articulatory images have not yet been established. Therefore, this article presents an approach to segment the tongue in two-dimensional magnetic resonance images and statistically model the segmented tongue shapes. The proposed approach assesses the articulator morphology based on an active shape model, which captures the shape variability of the tongue during speech production. To validate this new approach, a dataset of mid-sagittal magnetic resonance images acquired from four subjects was used, and key aspects of the shape of the tongue during the vocal production of relevant European Portuguese vowels were evaluated.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11