Automatic Tongue Delineation from MRI Images with a Convolutional Neural Network Approach
Fuente:
arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866916510719541248 |
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| author | Isaieva, Karyna Laprie, Yves Turpault, Nicolas Houssard, Alexis Felblinger, Jacques Vuissoz, Pierre-André |
| author_facet | Isaieva, Karyna Laprie, Yves Turpault, Nicolas Houssard, Alexis Felblinger, Jacques Vuissoz, Pierre-André |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_04893 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Automatic Tongue Delineation from MRI Images with a Convolutional Neural Network Approach Isaieva, Karyna Laprie, Yves Turpault, Nicolas Houssard, Alexis Felblinger, Jacques Vuissoz, Pierre-André Artificial Intelligence 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. |
| title | Automatic Tongue Delineation from MRI Images with a Convolutional Neural Network Approach |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2412.04893 |