Automatic Tongue Delineation from MRI Images with a Convolutional Neural Network Approach
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 21 references that are in the map. First posted on arXiv 6 Dec 2024.
Builds on
3 of 21 references.
References · 3
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
- 2015Holistically-Nested Edge Detectioncited by 592
- 2016Tongue contour extraction from ultrasound images based on deep neural networkcited by 2
Built on by
Not cited yet.