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.
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CITATION STYLE
Isaieva, K., Laprie, Y., Turpault, N., Houssard, A., Felblinger, J., & Vuissoz, P. A. (2020). Automatic Tongue Delineation from MRI Images with a Convolutional Neural Network Approach. Applied Artificial Intelligence, 34(14), 1115–1123. https://doi.org/10.1080/08839514.2020.1824090
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