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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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| Publicado no: | J Pers Med |
|---|---|
| Main Authors: | , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2021
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| Assuntos: | |
| Acesso em linha: | 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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