Application of deep learning-assisted anatomical structure segmentation based on CBCT in implant dentistry

doi:10.12337/zgkqzzxzz.2024.02.014

Abstract

Abstract: Compared with manual segmentation and traditional algorithm segmentation, the application of deep learning for oral anatomical structure segmentation can obtain accurate and consistent segmentation results efficiently. This approach can quickly obtain the anatomical structure information of the surgical areas to design implant surgery and restoration. This review provides an overview of the progress in CBCT-based deep learning for anatomical structure segmentation in the field of implant dentistry.

Key words: Implant dentistry, Deep learning, Cone beam computed tomography, Anatomical structure, Segmentation

Gao Qiancheng, Li Xindong, Cao Mingguo, Liu Yunfeng. Application of deep learning-assisted anatomical structure segmentation based on CBCT in implant dentistry[J]. Chinese Journal of Oral Implantology, 2024, 29(1): 82-86.

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