Automatic 3D tooth segmentation using convolutional neural networks in harmonic parameter space
文献类型：期刊论文
| 作者 | Zhang, Jianda2,3; Li, Chunpeng3; Song, Qiang3; Gao, Lin3,4; Lai, Yu-Kun1 |
| 刊名 | GRAPHICAL MODELS
 |
| 出版日期 | 2020-05-01 |
| 卷号 | 109页码:10 |
| 关键词 | Tooth segmentation Convolutional neural networks Dental mesh Maximum flow Surface parameterization |
| ISSN号 | 1524-0703 |
| DOI | 10.1016/j.gmod.2020.101071 |
| 英文摘要 | Automatic segmentation of 3D tooth models into individual teeth is an important step in orthodontic CAD systems. 3D tooth segmentation is a mesh instance segmentation task. Complex geometric features on the surface of 3D tooth models often lead to failure of tooth boundary detection, so it is difficult to achieve automatic and accurate segmentation by traditional mesh segmentation methods. We propose a novel solution to address this problem. We map a 3D tooth model isomorphically to a 2D harmonic parameter space and convert it into an image. This allows us to use a CNN to learn a highly robust image segmentation model to achieve automated and accurate segmentation of 3D tooth models. Finally, we map the image segmentation mask back to the 3D tooth model and refine the segmentation result using an improved Fuzzy-Clustering-and-Cuts algorithm. Our method has been incorporated into an orthodontic CAD system, and performs well in practice. |
| 资助项目 | Science and Technology Service Network Initiative[KFJ-STS-ZDTP-070] ; Science and Technology Service Network Initiative[KFJ-STS-QYZD-129] ; National Key R&D Program of China[2018AAA0103002] ; Royal Society Newton Advanced Fellowship[NAF\R2\192151] ; Shenzhen Research Institute of Big Data[2019ORF01013] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000536855200005 |
| 出版者 | ACADEMIC PRESS INC ELSEVIER SCIENCE |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/15330]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Zhang, Jianda |
| 作者单位 | 1.Cardiff Univ, Sch Comp Sci & Informat, Cardiff, Wales 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 4.Shenzhen Res Inst Big Data, Shenzhen 518172, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Jianda,Li, Chunpeng,Song, Qiang,et al. Automatic 3D tooth segmentation using convolutional neural networks in harmonic parameter space[J]. GRAPHICAL MODELS,2020,109:10. |
| APA | Zhang, Jianda,Li, Chunpeng,Song, Qiang,Gao, Lin,&Lai, Yu-Kun.(2020).Automatic 3D tooth segmentation using convolutional neural networks in harmonic parameter space.GRAPHICAL MODELS,109,10. |
| MLA | Zhang, Jianda,et al."Automatic 3D tooth segmentation using convolutional neural networks in harmonic parameter space".GRAPHICAL MODELS 109(2020):10. |
入库方式： OAI收割
来源：计算技术研究所
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