Key point detection method for X-ray head shadow image

By constructing and fine-tuning deep learning models, combining unsupervised learning and a small amount of labeled data, a key point detection method for X-ray head images is provided, which solves the problems of inefficient data utilization and insufficient diagnostic accuracy in the prior art, and achieves rapid and accurate key point detection and treatment process monitoring, improving the diagnosis and treatment efficiency and surgical safety of oral and maxillofacial diseases.

CN119694540APending Publication Date: 2025-03-25ZHEJIANG SHUREN UNIV
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Patent Information

Application Number
CN202411768735.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-04
Publication Date
2025-03-25

AI Technical Summary

Technical Problem

The prior art has problems such as low data utilization efficiency, reliance on a large amount of labeled data, poor diagnosis timeliness, insufficient diagnosis accuracy, difficulty tracking of treatment process, lack of basis for treatment adjustments, and inaccurate preoperative planning in the detection of key points of X-ray head images, which affects the quality and efficiency of diagnosis and treatment of oral and maxillofacial diseases.

Method used

Through steps such as data collection and initial model construction, unsupervised learning and mining features, fine-tuning models with a small amount of labeled data, analysis of model features, data mining and statistical analysis, real-time detection system, continuous monitoring and adjustment of treatment process, and full assistance of oral and maxillofacial surgery, key point detection methods for X-ray head images are provided.

Benefits of technology

It improves the performance of key point detection, can quickly detect key points in X-ray head images, achieve timeliness and accuracy of diagnosis, support continuous monitoring and adjustment of the treatment process, and provide important auxiliary information for oral and maxillofacial surgery, improving the accuracy and safety of the surgery.

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Abstract

The invention discloses a key point detection method for an X-ray head shadow image, and relates to the technical field of medical image processing, and the method comprises the following steps: data collection and initial model construction, unsupervised learning and feature mining, and fine adjustment of the model by using a small amount of labeled data; analyzing based on model features; assisting data mining and statistical analysis; detecting a system assistance diagnosis decision in real time; according to the method, the model automatically learns effective features and modes from a large number of unlabeled X-ray head shadow images, and then a small amount of labeled data is used for fine tuning, so that the performance of key point detection is improved; more disease modes and laws can be found; meanwhile, a key point detection result can be immediately obtained after an x-ray film of a patient is shot, so that diagnosis and treatment decision making can be carried out in time; the system can also be combined with a treatment process to realize real-time monitoring and feedback of a treatment effect and timely adjust a treatment plan; doctors are helped to operate more accurately, operation risks are reduced, and the operation success rate is increased.
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