Artificial Intelligence for the Computer-aided Detection of Periapical Lesions in Cone-beam Computed Tomographic Images.

Journal: Journal of endodontics
Published Date: May 8, 2020

Abstract

INTRODUCTION: The aim of this study was to use a Deep Learning (DL) algorithm for the automated segmentation of cone-beam computed tomographic (CBCT) images and the detection of periapical lesions.

Authors

  • Frank C Setzer
    Department of Endodontics, School of Dental Medicine, University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address: fsetzer@upenn.edu.
  • Katherine J Shi
    Private Practice, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Zhiyang Zhang
    Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
  • Hao Yan
    Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas 75235.
  • Hyunsoo Yoon
    Department of Industrial Engineering, Yonsei University, Seoul, Republic of Korea.
  • Mel Mupparapu
  • Jing Li
    Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.

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