Automated Segmentation of Upper Airways from MRI

Antti Ojalammi; Jarmo Malinen

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Paper

Automated Segmentation of Upper Airways from MRI

Topics: Image Processing Methods; Magnetic Resonance Imaging (MRI)

In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOSTEC, 77-84, 2017 , Porto, Portugal

Authors: Antti Ojalammi and Jarmo Malinen

Affiliation: Aalto University, Finland

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

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. In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - BIOIMAGING; ISBN 978-989-758-215-8; ISSN 2184-4305, SciTePress, pages 77-84. DOI: 10.5220/0006138300770084

@conference{bioimaging17,
author={Antti Ojalammi. and Jarmo Malinen.},
title={Automated Segmentation of Upper Airways from MRI},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - BIOIMAGING},
year={2017},
pages={77-84},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006138300770084},
isbn={978-989-758-215-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - BIOIMAGING
TI - Automated Segmentation of Upper Airways from MRI
SN - 978-989-758-215-8
IS - 2184-4305
AU - Ojalammi, A.
AU - Malinen, J.
PY - 2017
SP - 77
EP - 84
DO - 10.5220/0006138300770084
PB - SciTePress