Key point extraction and bone age prediction method in hip joint images

Abstract

The invention discloses a key point extraction and bone age prediction method in a hip joint image, and the related key point extraction comprises the steps: carrying out the feature extraction of thehip joint image through a feature extraction network, and obtaining a thermodynamic diagram of a C channel through down-sampling; wherein the feature extraction network is trained in advance by utilizing hip joint images containing key point positions marked by experts; according to the thermodynamic values, detecting N positions with the highest thermodynamic values from the thermodynamic diagram of the C channel to serve as key points; wherein C and N are both natural numbers, and C is greater than N; and compensating the position deviation of the N key points caused in the down-sampling stage by predicting the key point deviation loss to obtain the final positions of the N key points. According to the method, the key points can be accurately and quickly extracted, the working intensityis greatly reduced, and bone age prediction can be realized.

Description

technical field [0001] The invention relates to the technical field of medical image analysis, in particular to a method for key point extraction and bone age prediction in hip joint images. Background technique [0002] At present, the analysis and processing of medical images mostly rely on manual methods. [0003] On the one hand, the accuracy of the analysis results depends entirely on the technical level of the staff. Different staff may produce different analysis results for the same medical image. For some scientific research institutions, different analysis results or analysis whose accuracy is difficult to measure The results will affect the development of follow-up scientific research work; at the same time, for some grassroots hospitals or related training structures, different analysis results or analysis results whose accuracy is difficult to measure will also have a negative impact on the training goals of new staff. [0004] On the other hand, due to the comp...

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Problems solved by technology

[0003] On the one hand, the accuracy of the analysis results depends entirely on the technical level of the staff. Different staff may produce different analysis results for the same medical image. For some scientific research institutions, different analysis results or analysis whose accuracy is difficult to measure The results will affect the development of follow-up scientific research work; at the same time, for some grassroots hospitals or related training structures, different analysis results or analysis results whose accuracy is difficult to measure will also have a negative impact on the training goals of new staff

[0004] On the other hand, due to the complete reliance on manual methods, the analysis efficiency is low and the work intensity is high

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