Utilize este identificador para referenciar este registo:
https://hdl.handle.net/10216/111091
Autor(es): | Jessica C. Delmoral Sandra M. Rua Ventura João Manuel R. S. Tavares |
Título: | Segmentation of tongue shapes during vowel production in magnetic resonance images based on statistical modelling |
Data de publicação: | 2018-03 |
Resumo: | 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. |
Assunto: | Ciências Tecnológicas, Ciências da engenharia e tecnologias Technological sciences, Engineering and technology |
Áreas do conhecimento: | Ciências da engenharia e tecnologias Engineering and technology |
URI: | https://hdl.handle.net/10216/111091 |
Tipo de Documento: | Artigo em Revista Científica Internacional |
Condições de Acesso: | openAccess |
Aparece nas coleções: | FEUP - Artigo em Revista Científica Internacional |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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257222.1.pdf | Paper Draft | 2.9 MB | Adobe PDF | Ver/Abrir |
257222.jpg | 1st page | 162.52 kB | JPEG | Ver/Abrir |
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