A two-stage deep learning architecture for radiographic staging of periodontal bone loss.

Journal: BMC oral health
PMID: 35365122

Abstract

BACKGROUND: Radiographic periodontal bone loss is one of the most important basis for periodontitis staging, with problems such as limited accuracy, inconsistency, and low efficiency in imaging diagnosis. Deep learning network may be a solution to improve the accuracy and efficiency of periodontitis imaging staging diagnosis. This study aims to establish a comprehensive and accurate radiological staging model of periodontal alveolar bone loss based on panoramic images.

Authors

  • Linhong Jiang
    Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, China.
  • Daqian Chen
    School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, 310006, China.
  • Zheng Cao
    College of Computer Science and Technology, Zhejiang University, Hangzhou, 310006, China.
  • Fuli Wu
    School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, 310006, China.
  • Haihua Zhu
    Hospital of Stomatology of Zhejiang University, Hangzhou, 310018, China.
  • Fudong Zhu
    Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, China. zfd@zju.edu.cn.

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