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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...
Autores principales: | Wang, Xueling, Meng, Xianmin, Yan, Shu |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
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 |
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