Conference Paper 2015

A statistical shape space model of the palate surface trained on 3D MRI scans of the vocal tract

Palate

We describe a minimally-supervised method for computing a statistical shape space model of the palate surface. The model is created from a corpus of volumetric magnetic resonance imaging (MRI) scans collected from 12 speakers. We extract a 3D mesh of the palate from each speaker, then train the model using principal component analysis (PCA). The palate model is then tested using 3D MRI from another corpus and evaluated using a high-resolution optical scan. We find that the error is low even when only a handful of measured coordinates are available. In both cases, our approach yields promising results. It can be applied to extract the palate shape from MRI data, and could be useful to other analysis modalities, such as electromagnetic articulography (EMA) and ultrasound tongue imaging (UTI).

Author(s): Alexander Hewer and Ingmar Steiner and Timo Bolkart and Stefanie Wuhrer and Korin Richmond
Book Title: International Congress of Phonetic Sciences
Year: 2015
Month: August
Bibtex Type: Conference Paper (inproceedings)
Event Name: 18th International Congress of Phonetic Sciences (ICPhS)
Event Place: Glasgow, UK
Electronic Archiving: grant_archive
Links:

BibTex

@inproceedings{Hewer_ICPhS_2015,
  title = {A statistical shape space model of the palate surface trained on 3D MRI scans of the vocal tract },
  booktitle = {International Congress of Phonetic Sciences},
  abstract = {We describe a minimally-supervised method for computing a statistical shape space model of the palate surface. The model is created from a corpus of volumetric magnetic resonance imaging (MRI) scans collected from 12 speakers. We extract a 3D mesh of the palate from each speaker, then train the model using principal component analysis (PCA). The palate model is then tested using 3D MRI from another corpus and evaluated using a high-resolution optical scan. We find that the error is low even when only
  a handful of measured coordinates are available. In both cases, our approach yields promising results. It can be applied to extract the palate shape from MRI data, and could be useful to other analysis modalities, such as electromagnetic articulography (EMA) and ultrasound tongue imaging (UTI).},
  month = aug,
  year = {2015},
  slug = {hewer_icphs_2015},
  author = {Hewer, Alexander and Steiner, Ingmar and Bolkart, Timo and Wuhrer, Stefanie and Richmond, Korin},
  month_numeric = {8}
}