Micro-Computed Tomography-Guided Artificial Intelligence for Pulp Cavity and Tooth Segmentation on Cone-beam Computed Tomography.

Journal: Journal of endodontics
Published Date: Sep 11, 2021

Abstract

INTRODUCTION: This study proposes a novel data pipeline based on micro-computed tomographic (micro-CT) data for training the U-Net network to realize the automatic and accurate segmentation of the pulp cavity and tooth on cone-beam computed tomographic (CBCT) images.

Authors

  • Xiang Lin
    Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, USA.
  • Yujie Fu
    Department of Endodontics, School and Hospital of Stomatology, Tongji University, Shanghai Engineering Research Center of Tooth Restoration and Regeneration, Shanghai, China.
  • Genqiang Ren
    College of Electronics and Information Engineering, Tongji University, Shanghai, China.
  • Xiaoyu Yang
    Beijing Jishuitan Hospital, Beijing, China.
  • Wei Duan
    School of Medicine, Deakin University, Victoria, Australia.
  • Yufei Chen
    College of Electronics and Information Engineering, Tongji University, Shanghai 200092, China. Electronic address: yufeichen@tongji.edu.cn.
  • Qi Zhang
    Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.

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