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
Auteurs principaux: Qiu, Bingjiang, Guo, Jiapan, Kraeima, Joep, Glas, Haye Hendrik, Zhang, Weichuan, Borra, Ronald J. H., Witjes, Max Johannes Hendrikus, van Ooijen, Peter M. A.
Format: Artigo
Langue:Inglês
Publié: MDPI 2021
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Article
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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