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Automatic Tooth Segmentation and 3D Reconstruction from Panoramic and Lateral Radiographs

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Pattern Recognition and Computer Vision (PRCV 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12305))

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Abstract

The panoramic and lateral radiographs are commonly used in orthodontic dentistry to acquire patient-specific tooth morphology for diagnosing and treatment planning. Considering the variational dentition configurations and image blurs caused by device-specific artefacts and structure overlapping, the robust tooth segmentation and 3D reconstruction from radiographs remain a challenging issue. We propose a deformable exemplar-based conditional random fields (CRF) model for tooth segmentation and 3D shape estimation from the panoramic and lateral radiographs. The shared tooth foreground in the lateral and the panoramic radiographs are utilized for consistent labeling. The 3D deformable exemplars are introduced to provide a regularization of tooth contours to improve the tooth parsing in noisy and ambiguous radiographs. We introduce an alternating optimization scheme to solve the discrete superpixel labels and the continuous deformation of the 3D exemplars simultaneously. Extensive experiments on clinically obtained radiographs demonstrate that the proposed approach is effective and efficient for both tooth segmentation and 3D shape estimation from the panoramic and lateral radiographs.

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Acknowledgments

This work was supported by NSFC 61876008.

Author information

Authors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Department of Machine Intelligence, Peking University, Beijing, China

    Mochen Yu, Diya Sun & Yuru Pei

  2. Luoyang Institute of Science and Technology, Luoyang, China

    Yuke Guo

  3. School of Stomatology, Peking University, Beijing, China

    Tianmin Xu

Authors
  1. Mochen Yu
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  2. Yuke Guo
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  3. Diya Sun
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  4. Yuru Pei
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  5. Tianmin Xu
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Corresponding author

Correspondence to Yuru Pei .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Yuxin Peng

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Qingshan Liu

  3. Dalian University of Technology, Dalian, China

    Huchuan Lu

  4. Chinese Academy of Sciences, Beijing, China

    Zhenan Sun

  5. Chinese Academy of Sciences, Beijing, China

    Chenglin Liu

  6. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Xilin Chen

  7. Peking University, Beijing, China

    Hongbin Zha

  8. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

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Yu, M., Guo, Y., Sun, D., Pei, Y., Xu, T. (2020). Automatic Tooth Segmentation and 3D Reconstruction from Panoramic and Lateral Radiographs. In: Peng, Y., et al. Pattern Recognition and Computer Vision. PRCV 2020. Lecture Notes in Computer Science(), vol 12305. Springer, Cham. https://doi.org/10.1007/978-3-030-60633-6_5

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  • DOI: https://doi.org/10.1007/978-3-030-60633-6_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60632-9

  • Online ISBN: 978-3-030-60633-6

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