Tooth Segmentation from Cone Beam Computed Tomography using Skeleton-guided V-Net

Author:

Lv Wenjing1ORCID,Niu Qunwen2ORCID,Wang Lanying1ORCID,Song Shuang1ORCID,Huo Jiahao1ORCID,Wang Lin2ORCID,Xiao Ruoxiu1ORCID

Affiliation:

1. University of Science and Technology Beijing, China

2. Chinese People's Liberation Army (PLA) General Hospital, China

Publisher

ACM

Reference15 articles.

1. Deep learning models in medical image analysis

2. Hung K F, Ai Q Y H, Wong L M, Current Applications of Deep Learning and Radiomics on CT and CBCT for Maxillofacial Diseases[J]. Diagnostics, 2022, 13(1): 110.

3. Im J, Kim J Y, Yu H S, Accuracy and efficiency of automatic tooth segmentation in digital dental models using deep learning[J]. Scientific reports, 2022, 12(1): 9429.

4. Jaskari J, Sahlsten J, Järnstedt J, Deep learning method for mandibular canal segmentation in dental cone beam computed tomography volumes[J]. Scientific reports, 2020, 10(1): 5842.

5. Polizzi A, Quinzi V, Ronsivalle V, Tooth automatic segmentation from CBCT images: a systematic review[J]. Clinical Oral Investigations, 2023, 1-16.

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