An Annotated Multi-Site and Multi-Contrast Magnetic Resonance Imaging Dataset for the study of the Human Tongue Musculature.
Authors
Affiliations (17)
Affiliations (17)
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia. [email protected].
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia.
- Griffith School of Medicine and Dentistry, Brisbane, Queensland, Australia.
- Neuroscience Research Australia, Sydney, NSW, Australia.
- Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
- Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Queensland, Australia.
- University of Queensland Centre for Clinical Research, Brisbane, Queensland, Australia.
- School of Biomedical Sciences, The University of Queensland, Brisbane, Queensland, Australia.
- Scientia Professor of Neuroscience, The University of New South Wales, Sydney, NSW, Australia.
- Department of Neurology, Southeastern Sydney Local Health District, Sydney, NSW, Australia.
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Queensland, Australia.
- ARC Training Centre for Innovation in Biomedical Imaging and Technology (CIBIT), Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia.
- Queensland Digital Health Centre (QDHeC), The University of Queensland, Brisbane, Queensland, Australia.
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia. [email protected].
- Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia. [email protected].
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Queensland, Australia. [email protected].
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.