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Method and device for identifying periapical periodontitis of panoramic film based on deep learning

An apical periodontitis, deep learning technology, applied in neural learning methods, character and pattern recognition, understanding of medical/anatomical patterns, etc., can solve problems such as eye fatigue, inconsistency of manual diagnosis, inefficiency , to achieve good repeatability

Inactive Publication Date: 2019-07-02
北京羽医甘蓝信息技术有限公司
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] As one of the common oral diseases, apical periodontitis is mainly diagnosed by taking panoramic films in the periapical area of ​​the tooth. However, in view of the shortcomings of inconsistency and inefficiency in manual diagnosis
What's more, my country's medical resources are relatively scarce, and the number of senior medical experts is insufficient. If relying entirely on manual work, the operator's eyes will be tired, and the accuracy and credibility of the judgment results will be further reduced.

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  • Method and device for identifying periapical periodontitis of panoramic film based on deep learning
  • Method and device for identifying periapical periodontitis of panoramic film based on deep learning
  • Method and device for identifying periapical periodontitis of panoramic film based on deep learning

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Embodiment Construction

[0021] figure 1 It is a schematic flowchart of the deep learning-based method for identifying periapical periodontitis on panoramic films according to an embodiment of the present invention, including the following steps A to C.

[0022] Step A: Input the panorama into the permanent tooth segmentation model based on deep learning to obtain the permanent tooth segmentation result.

[0023] Optionally, the permanent tooth segmentation model based on deep learning in step A is obtained in the following manner: (1) Model design stage: the network structure includes an encoder part and a decoder part, the encoder part adopts the Xception network structure, and the decoding The FPN multi-scale fusion structure is used in the part of the encoder, and five convolutional layers of different depths are extracted from the encoder part as input, and the scSE structure is added to the up-sampling layer of the decoder part; (2) Model training stage: training for permanent teeth segmentation...

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Abstract

The invention provides a method and device for identifying panoramic film root periapical periodontitis based on deep learning. The method comprises the following steps: inputting a panorama into a constant-tooth segmentation model based on deep learning to obtain a constant-tooth segmentation result; determining a tooth root tip area image block corresponding to each tooth in the constant tooth segmentation result; and inputting the tooth root tip region image block into a deep learning-based periapical periarthritis focus segmentation model to obtain a periapical periarthritis focus segmentation result.

Description

technical field [0001] The present invention relates to the technical field of computer image processing, in particular to a method and device for identifying periapical periodontitis on panoramic films based on deep learning. Background technique [0002] Oral panoramic film is the main basis for oral diagnosis, which can clearly and completely display the whole picture of maxilla, mandible, upper and lower jaw dentition, alveolar bone, maxillary sinus cavity, sinus wall, sinus floor and temporomandibular Joint conditions, and provide accurate and effective help for the diagnosis of diseases around the jaw. [0003] As one of the common oral diseases, apical periodontitis is mainly diagnosed by taking panoramic films in the periapical area of ​​the tooth. However, manual diagnosis has the disadvantages of inconsistency and inefficiency. What's more, my country's medical resources are relatively scarce, and the number of senior medical experts is insufficient. If relying en...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06T7/155G06K9/62G06N3/04G06N3/08
CPCG06T7/0012G06T7/11G06T7/155G06N3/08G06T2207/30036G06V2201/03G06N3/045G06F18/241
Inventor 徐子能白海龙丁鹏汪子晨
Owner 北京羽医甘蓝信息技术有限公司