3D morphometric quantification of maxillae and defects for patients with unilateral cleft palate via deep learning-based CBCT image auto-segmentation.

Journal: Orthodontics & craniofacial research
Published Date: Mar 25, 2021

Abstract

OBJECTIVE: This study aimed to quantify the 3D asymmetry of the maxilla in patients with unilateral cleft lip and palate (UCP) and investigate the defect factors responsible for the variability of the maxilla on the cleft side using a deep-learning-based CBCT image segmentation protocol.

Authors

  • Xiaoyu Wang
    Department of Statistics Florida State University Tallahassee, FL, USA.
  • Matthew Pastewait
    United States Air Force, Kadena AB, Kadena, Japan.
  • Tai-Hsien Wu
  • Chunfeng Lian
    Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. Electronic address: chunfeng_lian@med.unc.edu.
  • Beatriz Tejera
  • Yan-Ting Lee
  • Feng-Chang Lin
  • Li Wang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Dinggang Shen
    School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.
  • Song Li
    Department of Crop and Soil Environmental Sciences, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.
  • Ching-Chang Ko

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