Convolutional neural network for automatic maxillary sinus segmentation on cone-beam computed tomographic images

An accurate three-dimensional (3D) segmentation of the maxillary sinus is crucial for multiple diagnostic and treatment applications. Yet, it is challenging and time-consuming when manually performed on a cone-beam computed tomography (CBCT) dataset. Recently, convolutional neural networks (CNNs) ha...

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Detalles Bibliográficos
Autores principales: Morgan, Nermin, Van Gerven, Adriaan, Smolders, Andreas, de Faria Vasconcelos, Karla, Willems, Holger, Jacobs, Reinhilde
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9079060/
https://www.ncbi.nlm.nih.gov/pubmed/35525857
http://dx.doi.org/10.1038/s41598-022-11483-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9079060/
https://www.ncbi.nlm.nih.gov/pubmed/35525857
http://dx.doi.org/10.1038/s41598-022-11483-3

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