Bone age evaluating method

Abstract

The invention discloses a bone age evaluating method which comprises the steps of based on an attention mechanism, mining a plurality of interested bone areas in a characteristic graph of an originalmetacarpal bone image X; based on an identification mechanism, identifying a plurality of interested bone areas which satisfy a requirement in the plurality of interested bone areas, and splicing theidentified characteristic graph of the plurality of interested bone areas with the characteristic graph of the original metacarpal bone image X for obtaining a characteristic vector C; and finally, after integrating the characteristic graph of each identified interested bone area, the characteristic graph of the original metacarpal bone image X and the characteristic vector C through a full connecting layer, performing bone age predicting, and integrating all predicting results for obtaining a bone age evaluating result. The bone age evaluating method realizes relatively high accuracy and relatively high evaluation speed.

Description

technical field [0001] The invention relates to the technical field of medical image analysis, in particular to a bone age assessment method. Background technique [0002] The traditional bone age assessment usually takes X-rays of the subject's left palm and wrist, and then conducts bone age assessment with the help of common standards. This process relies heavily on the practitioner's experience and is also time-consuming. In addition, there are great differences in skeletal development under different races, climates and other conditions, so the corresponding standards also vary widely, which increases the complexity of bone age assessment. [0003] In order to speed up diagnosis, improve diagnostic accuracy and reduce the burden on doctors, computer-aided diagnosis (CAD) based on artificial intelligence came into being, and achieved a higher accuracy than human experts in bone age assessment. However, most of these artificial intelligence technologies introduce specifi...

AI Technical Summary

Problems solved by technology

However, most of these artificial intelligence technologies introduce specific standards, focus on specific skeletal parts (such as wrist bones, proximal phalanges, etc.) through detection and segmentation methods, which limits the generalization ability of the model, and the model cannot Terminal training, thus affecting the accuracy of evaluation results

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