Bone age assessment method

Abstract

The invention discloses a bone age assessment method, which is characterized by comprising the steps of A, acquiring X-ray images of a plurality of target bone parts, and grading the acquired X-ray images according to the age group; B, performing feature extraction on a plurality of X-ray images in each grade, converting each grade of X-ray images into data by using a directional gradient histogram feature method, and building a mathematical model; and C, classifying the X-ray images in which the bone age is required to be assessed into the above grades by using a support vector machine classification algorithm. According to the bone age assessment method disclosed by the invention, an image processing technology and a computer vision technology are combined, and judgment for the bone maturity is realized through an interactive or automatic method.

Description

technical field [0001] The present invention relates to bone age assessment method. Background technique [0002] It is generally believed at home and abroad that judging the maturity of a developing individual based on bone age is an effective method, which can reflect the physiological state of the body more comprehensively, and it represents the biological developmental age to a large extent. Skeletal maturity indicates the level of growth and development of children characterized by a certain age, and is the most reliable indicator for evaluating individual growth and development. [0003] At present, bone age researchers generally use the method of taking X-ray films of a single joint of the body (such as the wrist joint) or major joints of the body (shoulder, elbow, wrist, hip, knee, ankle, etc.) to evaluate skeletal maturity. To sum up, the methods currently used in bone age estimation include atlas method, scoring method, measurement method and mathematical model me...

AI Technical Summary

Problems solved by technology

The traditional bone age assessment method is completed by comparing the results of expert reading with the standard atlas or assigning points according to the degree of epiphyseal development, but the scores are highly subjective, which is not conducive to the objective evaluation of bone age

Moreover, due to the need to compare or score the bones of multi-joint parts, manual processing takes a long time, and the professional knowledge of the scorer is required to be high

Therefore, there are more or less some reading errors through manual reading, and these errors will have a "larger" or "smaller" impact on the bone age assessment results

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