Application of a fully deep convolutional neural network to the automation of tooth segmentation on panoramic radiographs.

Journal: Oral surgery, oral medicine, oral pathology and oral radiology
Published Date: Nov 15, 2019

Abstract

OBJECTIVES: To evaluate a fully deep learning mask region-based convolutional neural network (R-CNN) method for automated tooth segmentation using individual annotation of panoramic radiographs.

Authors

  • Jeong-Hee Lee
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea.
  • Sang-Sun Han
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea. Electronic address: sshan@yuhs.ac.
  • Young Hyun Kim
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea.
  • Chena Lee
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea.
  • Inhyeok Kim
    Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea.

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