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

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 (f...

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Main Authors: Fernanda L. Ribeiro, Xiangyun Zhu, Xincheng Ye, Sicong Tu, Shyuan T. Ngo, Robert D. Henderson, Frederik J. Steyn, Matthew C. Kiernan, Markus Barth, Steffen Bollmann, Thomas B. Shaw
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-025-05092-8
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author Fernanda L. Ribeiro
Xiangyun Zhu
Xincheng Ye
Sicong Tu
Shyuan T. Ngo
Robert D. Henderson
Frederik J. Steyn
Matthew C. Kiernan
Markus Barth
Steffen Bollmann
Thomas B. Shaw
author_facet Fernanda L. Ribeiro
Xiangyun Zhu
Xincheng Ye
Sicong Tu
Shyuan T. Ngo
Robert D. Henderson
Frederik J. Steyn
Matthew C. Kiernan
Markus Barth
Steffen Bollmann
Thomas B. Shaw
author_sort Fernanda L. Ribeiro
collection DOAJ
description 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.
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spelling doaj-art-559f760d808f4ceea0c78926366acba62025-08-20T03:53:57ZengNature PortfolioScientific Data2052-44632025-05-011211910.1038/s41597-025-05092-8An Annotated Multi-Site and Multi-Contrast Magnetic Resonance Imaging Dataset for the study of the Human Tongue MusculatureFernanda L. Ribeiro0Xiangyun Zhu1Xincheng Ye2Sicong Tu3Shyuan T. Ngo4Robert D. Henderson5Frederik J. Steyn6Matthew C. Kiernan7Markus Barth8Steffen Bollmann9Thomas B. Shaw10School of Electrical Engineering and Computer Science, The University of QueenslandSchool of Electrical Engineering and Computer Science, The University of QueenslandSchool of Electrical Engineering and Computer Science, The University of QueenslandNeuroscience Research AustraliaRoyal Brisbane and Women’s HospitalRoyal Brisbane and Women’s HospitalRoyal Brisbane and Women’s HospitalNeuroscience Research AustraliaSchool of Electrical Engineering and Computer Science, The University of QueenslandSchool of Electrical Engineering and Computer Science, The University of QueenslandSchool of Electrical Engineering and Computer Science, The University of QueenslandAbstract 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.https://doi.org/10.1038/s41597-025-05092-8
spellingShingle Fernanda L. Ribeiro
Xiangyun Zhu
Xincheng Ye
Sicong Tu
Shyuan T. Ngo
Robert D. Henderson
Frederik J. Steyn
Matthew C. Kiernan
Markus Barth
Steffen Bollmann
Thomas B. Shaw
An Annotated Multi-Site and Multi-Contrast Magnetic Resonance Imaging Dataset for the study of the Human Tongue Musculature
Scientific Data
title An Annotated Multi-Site and Multi-Contrast Magnetic Resonance Imaging Dataset for the study of the Human Tongue Musculature
title_full An Annotated Multi-Site and Multi-Contrast Magnetic Resonance Imaging Dataset for the study of the Human Tongue Musculature
title_fullStr An Annotated Multi-Site and Multi-Contrast Magnetic Resonance Imaging Dataset for the study of the Human Tongue Musculature
title_full_unstemmed An Annotated Multi-Site and Multi-Contrast Magnetic Resonance Imaging Dataset for the study of the Human Tongue Musculature
title_short An Annotated Multi-Site and Multi-Contrast Magnetic Resonance Imaging Dataset for the study of the Human Tongue Musculature
title_sort annotated multi site and multi contrast magnetic resonance imaging dataset for the study of the human tongue musculature
url https://doi.org/10.1038/s41597-025-05092-8
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