@article{d3b8a3dd3186409f9c51bf144635860f,
title = "Machine learning in orthodontics: Introducing a 3D auto-segmentation and auto-landmark finder of CBCT images to assess maxillary constriction in unilateral impacted canine patients",
abstract = "Objectives: To (1) introduce a novel machine learning method and (2) assess maxillary structure variation in unilateral canine impaction for advancing clinically viable information. Materials and Methods: A machine learning algorithm utilizing Learning-based multi-source IntegratioN frameworK for Segmentation (LINKS) was used with cone-beam computed tomography (CBCT) images to quantify volumetric skeletal maxilla discrepancies of 30 study group (SG) patients with unilaterally impacted maxillary canines and 30 healthy control group (CG) subjects. Fully automatic segmentation was implemented for maxilla isolation, and maxillary volumetric and linear measurements were performed. Analysis of variance was used for statistical evaluation. Results: Maxillary structure was successfully auto-segmented, with an average dice ratio of 0.80 for three-dimensional image segmentations and a minimal mean difference of two voxels on the midsagittal plane for digitized landmarks between the manually identified and the machine learning–based (LINKS) methods. No significant difference in bone volume was found between impaction ([2.37 6 0.34] 3 104 mm3) and nonimpaction ([2.36 6 0.35] 3 104 mm3) sides of SG. The SG maxillae had significantly smaller volumes, widths, heights, and depths (P, .05) than CG. Conclusions: The data suggest that palatal expansion could be beneficial for those with unilateral canine impaction, as underdevelopment of the maxilla often accompanies that condition in the early teen years. Fast and efficient CBCT image segmentation will allow large clinical data sets to be analyzed effectively.",
keywords = "CBCT, Canine impaction, Image segmentation, Machine learning, Orthodontics",
author = "Si Chen and Li Wang and Gang Li and Wu, {Tai Hsien} and Shannon Diachina and Beatriz Tejera and Kwon, {Jane Jungeun} and Lin, {Feng Chang} and Lee, {Yan Ting} and Tianmin Xu and Dinggang Shen and Ko, {Ching Chang}",
note = "Funding Information: aAssociate Professor, Department of Orthodontics, Peking University School and Hospital of Stomatology, PR China; and Visiting Scholar, Oral and Craniofacial Health Sciences Research, School of Dentistry, University of North Carolina, Chapel Hill, NC. bAssistant Professor, Department of Radiology; and Biomedical Research Imaging Center School of Medicine, University of North Carolina, Chapel Hill, NC. c Assistant Professor, Biomedical Research Imaging Center, School of Medicine, University of North Carolina, Chapel Hill, NC. d Postdoctoral Researcher, Oral and Craniofacial Health Sciences Research, School of Dentistry, University of North Carolina, Chapel Hill, NC. e Research Assistant, Oral and Craniofacial Health Sciences Research, School of Dentistry, University of North Carolina, Chapel Hill, NC. f Dental Student, Oral and Craniofacial Health Sciences Research, School of Dentistry, University of North Carolina, Chapel Hill, NC. g Associate Professor, Department of Biostatistics, University of North Carolina, Chapel Hill, NC. h Professor, Department of Orthodontics, Peking University School and Hospital of Stomatology, PR China. iProfessor, Department of Radiology; and Director, Biomedical Research Imaging Center, School of Medicine, University of North Carolina, Chapel Hill, NC. j Professor, Oral and Craniofacial Health Sciences Research; and Chair, Department of Orthodontics, School of Dentistry, University of North Carolina, Chapel Hill, NC. Corresponding author: Dr Ching-Chang Ko, School of Dentistry, Department of Orthodontics, 275 Brauer Hall, CB# 7450, Chapel Hill, NC 25799 (e-mail: Ching-Chang_Ko@unc.edu) Accepted: May 2019. Submitted: January 2019. Published Online: August 12, 2019 {\textcopyright} 2020 by The EH Angle Education and Research Foundation, Inc. Funding Information: This study was supported, in part, by NIH/NIDCR R01DE022816 and Peking University Medicine Seed Fund for Interdisciplinary Research BMU2018MI013. Publisher Copyright: {\textcopyright} 2020 by The EH Angle Education and Research Foundation, Inc.",
year = "2020",
month = jan,
doi = "10.2319/012919-59.1",
language = "English",
volume = "90",
pages = "77--84",
journal = "Angle Orthodontist",
issn = "0003-3219",
publisher = "E H Angle Orthodontists Research & Education Foundation, Inc.",
number = "1",
}