Intelligent analysis method for oral medical image

By analyzing multi-time-point images and dental plaque data of periodontitis, key anatomical regions of periodontitis are identified, and quantitative indicators and gradient characteristics of tooth changes are calculated. This solves the problem of low accuracy in dynamic risk prediction of periodontitis in existing technologies, and enables early risk warning and individualized assessment.

CN121860980AInactive Publication Date: 2026-04-14URUMQI STOMATOLOGICAL HOSPITAL
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Patent Information

Application Number
CN202512046214.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-31
Publication Date
2026-04-14
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Existing technologies cannot perform individualized and dynamic risk prediction, and fail to effectively consider changes in interdental spaces, tooth displacement, and real-time plaque activity in periodontitis imaging analysis, resulting in low accuracy in predicting the risk of insidious periodontitis development.

Method used

By acquiring multi-time-point sequential images of periodontitis within a historical period, key anatomical regions of periodontitis are identified, periodontitis sensitivity parameters and quantitative indicators of change are calculated, spatial gradient features and temporal gradient features are analyzed, and cluster analysis and risk labeling are performed in conjunction with dental plaque staining detection data to achieve dynamic prediction of multi-dimensional gradient feature vectors.

Benefits of technology

It enables in-depth exploration and early warning of the hidden risks of periodontitis, improves the accuracy of individualized risk prediction, captures early changes in the micromechanical environment, and provides more accurate risk assessment.

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Abstract

The invention relates to the technical field of image recognition, in particular to an intelligent oral medical image analysis method, which comprises the following steps: acquiring oral medical images of periodontitis in a historical period, and marking periodontitis-related key anatomical regions to obtain periodontitis sensitive parameters; calculating a change quantitative index of periodontitis sensitive parameters, analyzing a space gradient feature and a time gradient feature, and further determining a multi-dimensional gradient feature vector of each tooth; performing clustering analysis based on the multi-dimensional gradient feature vector to determine a typical mode feature vector; obtaining the oral medical image of the current period to determine the multi-dimensional gradient feature vector of each tooth; calculating the distance between the multi-dimensional gradient feature vector of the current period and the typical mode feature vector, and marking a potential hidden risk unit; acquiring dental plaque staining detection data of the current period; and marking a potential concealment risk correction unit based on the dental plaque staining detection data. The periodontitis latent development risk prediction precision of the individual is improved.
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