Tooth instance segmentation based on capturing dependencies and receptive field adjustment in cone beam computed tomography-Reference-Cited by-同舟云学术

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Tooth instance segmentation based on capturing dependencies and receptive field adjustment in cone beam computed tomography

Published:2022-07-31 Issue:5 Volume:33 Page:
ISSN:1546-4261
Container-title:Computer Animation and Virtual Worlds
language:en
Short-container-title:Computer Animation & Virtual

Author:

Dou Wenhan¹^ORCID,Gao Shanshan¹²³,Mao Deqian¹,Dai Honghao¹,Zhang Chenhao¹,Zhou Yuanfeng⁴

Affiliation:

1. School of Computer Science and Technology Shandong University of Finance and Economics Jinan China

2. Shandong China‐U.S. Digital Media International Cooperation Research Center Jinan China

3. Shandong Provincial Key Laboratory of Digital Media Technology Jinan China

4. School of Software Shandong University Jinan China

Funder

National Natural Science Foundation of China

Key Research and Development Program of Shandong Province

Publisher

Wiley

Subject

Computer Graphics and Computer-Aided Design,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cav.2100

Reference26 articles.

1. TSegNet: An efficient and accurate tooth segmentation network on 3D dental model

2. EvainT RipocheX AtifJ BlochI.Semi‐automatic teeth segmentation in cone‐beam computed tomography by graph‐cut with statistical shape priors. Proceedings of the IEEE 14th International Symposium on Biomedical Imaging (ISBI) Melbourne VIC Australia; April 2017. p. 1197–200.

3. Automated segmentation of dental CBCT image with prior-guided sequential random forests

4. Tooth and Alveolar Bone Segmentation From Dental Computed Tomography Images

5. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model

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1. The Application of Artificial Intelligence for Tooth Segmentation in CBCT Images: A Systematic Review;Applied Sciences;2024-07-19

2. SimpleMask: parameter link and efficient instance segmentation;The Visual Computer;2024-05-24

3. Semi or fully automatic tooth segmentation in CBCT images: a review;PeerJ Computer Science;2024-04-19

4. Automatic tooth segmentation for patients with alveolar clefts guided by tooth descriptors;Biomedical Signal Processing and Control;2024-04

5. BENet: boundary-enhanced network for real-time semantic segmentation;The Visual Computer;2024-03-27

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