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

Autor:	Karyna Isaieva, Yves Laprie, Nicolas Turpault, Alexis Houssard, Jacques Felblinger, Pierre-André Vuissoz
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	Electronic computers. Computer science QA75.5-76.95 Cybernetics Q300-390
Zdroj:	Applied Artificial Intelligence, Vol 34, Iss 14, Pp 1115-1123 (2020)
Druh dokumentu:	article
ISSN:	0883-9514 1087-6545 08839514
DOI:	10.1080/08839514.2020.1824090
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/658b9160b50f4960a537fe6b74ce6b85 Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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