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An automatic tooth reconstruction method based on multimodal data

机译:基于多模式数据的自动齿重建方法

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摘要

A complete digital tooth model with both the dental crown and root is of great importance for computer-aided orthodontic treatment. This paper first proposes an automatic segmentation method for complete tooth models with both the crown and reconstructed root based on multimodal data. With the laser-scanned crown mesh and cone-beam computed tomography (CBCT) data of a patient, we propose an improved iterative closest point algorithm and convex hull selection method to obtain the initial contour and slice for segmentation. Based on the initialization, we propose an improved level set method with the shape prior, named LSS, to segment the root of the tooth slice by slice. After segmentation, we reconstruct the root model and replace the crown part with the scanned crown model to solve the occlusal problem. The experiments demonstrate that our method can obtain tooth models from CBCT automatically and accurately.
机译:具有牙科冠和根系的完整数字齿模型对于计算机辅助性正畸治疗非常重要。本文首先提出了一种自动分段方法,用于基于多模式数据的具有冠和重建根的完整齿模型。利用患者的激光扫描冠网和锥形光束计算机断层扫描(CBCT)数据,我们提出了一种改进的迭代最接近点算法和凸壳选择方法,以获得分割的初始轮廓和切片。基于初始化,我们提出了一种改进的水平集方法,其形状名为LSS,以通过切片对牙切片的根进行分割。在分割之后,我们重建根模型并用扫描的冠模型更换冠部,以解决咬合问题。实验表明,我们的方法可以自动准确地从CBCT获得牙齿模型。

著录项

  • 来源
    《Journal of visualization》 |2021年第1期|205-221|共17页
  • 作者单位

    State Key Laboratory of CAD & CG Zhejiang University Hangzhou China;

    State Key Laboratory of CAD & CG Zhejiang University Hangzhou China;

    State Key Laboratory of CAD & CG Zhejiang University Hangzhou China;

    State Key Laboratory of CAD & CG Zhejiang University Hangzhou China Innovation Center for Minimally Invasive Technique and Device Zhejiang University Hangzhou China;

    Department of Stomatology The First Affiliated Hospital College of Medicine Zhejiang University Hangzhou Chinal;

    State Key Laboratory of CAD & CG Zhejiang University Hangzhou China Innovation Center for Minimally Invasive Technique and Device Zhejiang University Hangzhou China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Automatic image segmentation; Iterative closest point; Convex hull; Improved level set; Shape prior; Multimodal data; Cone-beam computed tomography;

    机译:自动图像分割;迭代最近的点;凸壳;改进的水平集;以前的形状;多模式数据;锥梁计算断层扫描;
  • 入库时间 2022-08-18 23:31:36

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