An Annotated Multi-Site and Multi-Contrast Magnetic Resonance Imaging Dataset for the study of the Human Tongue Musculature.

Journal: Scientific data
Published Date:

Abstract

This dataset provides the first annotated, openly available MRI-based imaging dataset for investigations of tongue musculature, including multi-contrast and multi-site MRI data from non-disease participants. The present dataset includes 47 participants collated from three studies: BeLong (four participants; T2-weighted images), EATT4MND (19 participants; T2-weighted images), and BMC (24 participants; T1-weighted images). We provide manually corrected segmentations of five key tongue muscles: the superior longitudinal, combined transverse/vertical, genioglossus, and inferior longitudinal muscles. Other phenotypic measures, including age, sex, weight, height, and tongue muscle volume, are also available for use. This dataset will benefit researchers across domains interested in the structure and function of the tongue in health and disease. For instance, researchers can use this data to train new machine learning models for tongue segmentation, which can be leveraged for segmentation and tracking of different tongue muscles engaged in speech formation in health and disease. Altogether, this dataset provides the means to the scientific community for investigation of the intricate tongue musculature and its role in physiological processes and speech production.

Authors

  • Fernanda L Ribeiro
    School of Psychology, The University of Queensland, Saint Lucia, Brisbane, QLD 4072, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia. Electronic address: fernanda.ribeiro@uq.edu.au.
  • Xiangyun Zhu
    School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia.
  • Xincheng Ye
    School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia.
  • Sicong Tu
    Neuroscience Research Australia, Sydney, NSW, Australia.
  • Shyuan T Ngo
    Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
  • Robert D Henderson
    Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
  • Frederik J Steyn
    Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
  • Matthew C Kiernan
    Neuroscience Research Australia, Sydney, NSW, Australia.
  • Markus Barth
    Center for Advanced Imaging, University of Queensland, St Lucia, QLD, Australia.
  • Steffen Bollmann
    Centre for Advanced Imaging, The University of Queensland, Building 57 of University Dr, St Lucia, QLD 4072, Brisbane, Australia. Electronic address: steffen.bollmann@cai.uq.edu.au.
  • Thomas B Shaw
    School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia. t.shaw@uq.edu.au.