Int J Stomatol

Int J Stomatol ›› 2024, Vol. 51 ›› Issue (4): 483-488.doi: 10.7518/gjkq.2024063

• Reviews • Previous Articles    

Application progress of convolution neural network in endodontics

Xinyue Chen1(),Xiaoyu Pan2,Yan Yang1,Yuanyuan Jia2,Liang Chen1()   

  1. 1.Dept. of Endodontics, Stomatological Hospital of Chongqing Medical University, Chongqing 400000, China
    2.School of Medical Information, Chongqing Medical University, Chongqing 400000, China
  • Received:2023-07-26 Revised:2024-02-26 Online:2024-07-01 Published:2024-06-24
  • Contact: Liang Chen E-mail:2021120627@stu.cqmu.edu.cn;chenliang@hospital.cqmu.edu.cn
  • Supported by:
    General Program of Natural Science Foundation of Chongqing Municipality(CSTB2022NSCQ-MSX0128);Chongqing Postdoctoral Research Program(2021XM3062);Chongqing Medical University Future Medical Youth Innovation Team Support Program (W0034)

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Abstract:

In the information age with the rapid development of computer algorithms, the application of deep learning has received extensive attention in various fields. As one of the most typical network structures in deep learning, a convolutional neural network has outstanding learning ability and great adaptability and plays an important role especially in image recognition and processing. Meanwhile, in the development of endodontics, the application of convolutional neural networks has become increasingly common, such as in assisting doctors in the analysis, diagnosis, treatment, and prognosis evaluation of caries and periapical diseases. Such networks have contributed to alleviating the shortage of medical resources and promoting the development of endodontics. This paper mainly summarizes the application of convolutional neural networks in endodontics and looks forward to its future.

Key words: deep learning, convolution neural network, endodontics

CLC Number: 

  • R781.1

TrendMD: 

Fig 1

The specific structure of the ResNet model to accomplish the image classification task"

Fig 2

Schematic application of CNN model in caries diagnosis"

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