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

• Tipo: Artigo em Revista Científica Internacional
• Data: 2018-03

Autores

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

Revista

A Revista está pendente de validação pelos Serviços Administrativos.

Título: PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE

Vol. 232

Páginas: 271-281

ISSN: 0954-4119

Indexação

ISI Web of Knowledge - 0 Citações

ISI Web of Science

Scopus - 1 Citação

INSPEC

Classificação Científica

CORDIS: Ciências Tecnológicas

FOS: Ciências da engenharia e tecnologias

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11