Deep Learning-Based Image Segmentation of Cone-Beam Computed Tomography Images for Oral Lesion Detection

This paper aimed to study the adoption of deep learning (DL) algorithm of oral lesions for segmentation of cone-beam computed tomography (CBCT) images. 90 patients with oral lesions were taken as research subjects, and they were grouped into blank, control, and experimental groups, whose images were...

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Detalles Bibliográficos
Autores principales: Wang, Xueling, Meng, Xianmin, Yan, Shu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478545/
https://www.ncbi.nlm.nih.gov/pubmed/34594482
http://dx.doi.org/10.1155/2021/4603475

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478545/
https://www.ncbi.nlm.nih.gov/pubmed/34594482
http://dx.doi.org/10.1155/2021/4603475

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