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Automatic Tongue Delineation from MRI Images with a Convolutional Neural Network Approach

Authors :
Karyna Isaieva
Yves Laprie
Nicolas Turpault
Alexis Houssard
Jacques Felblinger
Pierre-André Vuissoz
Source :
Applied Artificial Intelligence, Vol 34, Iss 14, Pp 1115-1123 (2020)
Publication Year :
2020
Publisher :
Taylor & Francis Group, 2020.

Abstract

Tongue contour extraction from real-time magnetic resonance images is a nontrivial task due to the presence of artifacts manifesting in form of blurring or ghostly contours. In this work, we present results of automatic tongue delineation achieved by means of U-Net auto-encoder convolutional neural network. We present both intra- and inter-subject validation. We used real-time magnetic resonance images and manually annotated 1-pixel wide contours as inputs. Predicted probability maps were post-processed in order to obtain 1-pixel wide tongue contours. The results are very good and slightly outperform published results on automatic tongue segmentation.

Details

Language :
English
ISSN :
08839514 and 10876545
Volume :
34
Issue :
14
Database :
Directory of Open Access Journals
Journal :
Applied Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
edsdoj.658b9160b50f4960a537fe6b74ce6b85
Document Type :
article
Full Text :
https://doi.org/10.1080/08839514.2020.1824090