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Recurrent Convolutional Neural Networks for 3D Mandible Segmentation in Computed Tomography
Purpose: Classic encoder–decoder-based convolutional neural network (EDCNN) approaches cannot accurately segment detailed anatomical structures of the mandible in computed tomography (CT), for instance, condyles and coronoids of the mandible, which are often affected by noise and metal artifacts. Th...
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| Publié dans: | J Pers Med |
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| Auteurs principaux: | , , , , , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
MDPI
2021
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8229770/ https://ncbi.nlm.nih.gov/pubmed/34072714 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/jpm11060492 |
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