A deep-learning system for diagnosing ectopic eruption.

Journal: Journal of dentistry
PMID: 39424256

Abstract

OBJECTIVES: To construct a diagnostic model for mixed dentition using a multistage deep-learning network to predict potential ectopic eruption in permanent teeth by integrating dentition segmentation into the process of automatic classification of dental development stages.

Authors

  • Haojie Yu
    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, China.
  • Zheng Cao
    College of Computer Science and Technology, Zhejiang University, Hangzhou, 310006, China.
  • Gaozhi Pang
    College of Computer Science and Technology, Zhejiang University of Technology.Hangzhou, Zhejiang, 310023, 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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