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Authors: Antti Ojalammi and Jarmo Malinen

Affiliation: Aalto University, Finland

ISBN: 978-989-758-215-8

Keyword(s): MRI, 3D Image Processing, Automatic Surface Extraction, Vocal Tract.

Related Ontology Subjects/Areas/Topics: Bioimaging ; Biomedical Engineering ; Cardiovascular Imaging and Cardiography ; Cardiovascular Technologies ; Health Engineering and Technology Applications ; Image Processing Methods ; Magnetic Resonance Imaging ; NeuroSensing and Diagnosis ; Neurotechnology, Electronics and Informatics

Abstract: An algorithm for automatically extracting a triangulated surface mesh of the human vocal tract from 3D MRI data is proposed. The algorithm is based on a combination of anatomic landmarking, seeded region growing, and smoothing. Using these methods, a mask is automatically created for removing unwanted details not associated with the vocal tract from the MRI voxel data. The mask is then applied to the original MRI data, after which marching cubes algorithm is used for extracting a triangulated surface. The proposed method can be used for processing large datasets, e.g., for validation of numerical methods in speech sciences as well as for anatomical studies.

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Paper citation in several formats:
Ojalammi, A. and Malinen, J. (2017). Automated Segmentation of Upper Airways from MRI - Vocal Tract Geometry Extraction.In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2 BIOIMAGING: BIOIMAGING, (BIOSTEC 2017) ISBN 978-989-758-215-8, pages 77-84. DOI: 10.5220/0006138300770084

@conference{bioimaging17,
author={Antti Ojalammi. and Jarmo Malinen.},
title={Automated Segmentation of Upper Airways from MRI - Vocal Tract Geometry Extraction},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2 BIOIMAGING: BIOIMAGING, (BIOSTEC 2017)},
year={2017},
pages={77-84},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006138300770084},
isbn={978-989-758-215-8},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2 BIOIMAGING: BIOIMAGING, (BIOSTEC 2017)
TI - Automated Segmentation of Upper Airways from MRI - Vocal Tract Geometry Extraction
SN - 978-989-758-215-8
AU - Ojalammi, A.
AU - Malinen, J.
PY - 2017
SP - 77
EP - 84
DO - 10.5220/0006138300770084

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