Abnormal maxillary sinus diagnosing on CBCT images via object detection and 'straight-forward' classification deep learning strategy.

Journal: Journal of oral rehabilitation
PMID: 37665121

Abstract

BACKGROUND: Pathological maxillary sinus would affect implant treatment and even result in failure of maxillary sinus lift and implant surgery. However, the maxillary sinus abnormalities are challenging to be diagnosed through CBCT images, especially for young dentists or dentists in grassroots medical institutions without systematical education of general medicine.

Authors

  • 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.
  • Rihui Song
    School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China.
  • 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.
  • Haopeng Li
    School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China.
  • Shijie Chen
    Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China. shijiechencsu@csu.edu.cn.
  • 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.
  • Gengbin Cai
    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.
  • Kai Huang
  • 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.

Keywords

External Resources

Popular Topics
Recent Journals