Construction of an end-to-end regression neural network for the determination of a quantitative index sagittal root inclination.

Journal: Journal of periodontology
PMID:

Abstract

BACKGROUND: Immediate implant placement in the esthetic area requires comprehensive assessments with nearly 30 quantitative indexes. Most artificial intelligence (AI)-driven measurements of quantitative indexes depend on segmentation or landmark detection, which require extra labeling of images and contain possible intraclass errors.

Authors

  • Yixiong Lin
    Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University and Guangdong Research Center for Dental and Cranial Rehabilitation and Material Engineering, Guangzhou, China.
  • Mengru Shi
    Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University and Guangdong Research Center for Dental and Cranial Rehabilitation and Material Engineering, Guangzhou, China.
  • Dawei Xiang
    School of Mathematics, Sun Yat-sen University, Guangzhou, China.
  • Peisheng Zeng
    Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University and Guangdong Research Center for Dental and Cranial Rehabilitation and Material Engineering, Guangzhou, China.
  • Zhuohong Gong
    Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University and Guangdong Research Center for Dental and Cranial Rehabilitation and Material Engineering, Guangzhou, China.
  • Haiwen Liu
    Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University and Guangdong Research Center for Dental and Cranial Rehabilitation and Material Engineering, Guangzhou, China.
  • Quan Liu
    Vanderbilt University, Nashville, TN 37212, USA.
  • Zhuofan Chen
    Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University and Guangdong Research Center for Dental and Cranial Rehabilitation and Material Engineering, Guangzhou, China.
  • Juan Xia
    From the Department of Radiology, Wuhan Huangpi People's Hospital, Wuhan, China (L.L., Z.X., X.F., S.Z., Juan Xia); Jianghan University Affiliated Huangpi People's Hospital, Wuhan, China (L.L.); Department of Radiology, Wuhan Pulmonary Hospital, Wuhan, China (L.Q.); Keya Medical Technology Co, Ltd, Shenzhen, China (Y.Y., X.W., B.K., J.B., Y.L., Z.F., Q.S., K.C.); Department of Radiology, Liaocheng People's Hospital, Liaocheng, China (D.L.); Department of CT, The Third Medical Center of Chinese PLA General Hospital, Beijing, China (G.W.); and Department of Radiology, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen, China 518035 (Q.X., Jun Xia).
  • Zetao Chen
    School of Electrical Engineering and Computer Science, Queensland University of Technology, Australia; Australian Centre for Robotic Vision, Queensland University of Technology, Australia. Electronic address: zetao.chen@hdr.qut.edu.au.