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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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| Gepubliceerd in: | J Pers Med |
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| Hoofdauteurs: | , , , , , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
MDPI
2021
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| Onderwerpen: | |
| Online toegang: | 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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