A multi-classifier wrist bone grade recognition method based on height and age

A multi-classifier and recognition method technology, applied in the field of grade recognition, can solve the problem of low classification accuracy of each bone grade in the left hand, and achieve the effects of reducing the decline of model accuracy, reducing errors, and improving accuracy.

Active Publication Date: 2022-03-04
浙江康体汇科技有限公司
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Problems solved by technology

[0006] The purpose of the present invention is to overcome the problem that the existing deep learning model has a low classification accuracy rate for each bone grade of the left hand, and to provide a multi-classifier wrist bone grade recognition method based on height and age

Method used

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Experimental program
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Embodiment

[0018] The present embodiment provides a multi-classifier wrist bone grade recognition method based on height and age, comprising the following steps:

[0019] Step 1. Number the 14 bones in the X-ray of the wrist bone in sequence. The 14 bones are: radius, palm 1, palm 3, palm 5, near 1, near 3, near 5, middle 3, middle 5 , far 1, far 3, far 5, capitate, hamate, number these 14 bones from 1 to 14 in turn; use Ni to represent the total number of grades of the i-th bone in the CHN bone age assessment method, i= 1,...,14;

[0020] Step 2. For i=1, ..., 14 in turn, according to the actual situation, a batch of i-th bone slice sample sets whose height, age and grade have been calibrated are used to train to obtain a regression model Mi based on a deep learning network;

[0021] Step 3. For i=1,...,14 in turn, according to the actual situation, a batch of i-th bone slice sample sets whose bone grades have been calibrated are used to train to obtain the following three-category dee...

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Abstract

The invention discloses a multi-classifier wrist bone grade recognition method based on height and age. The method of the present invention is based on a deep learning network regression model based on the two information of height and age and a plurality of three-category deep learning network classification models, first obtains the approximate range of grades through the regression model, and then selects the corresponding classifier Accurate classification of bone grades. The present invention can effectively improve the accuracy of bone age grade judgment, thereby reducing the final bone age judgment error.

Description

technical field [0001] The invention relates to the technical field of bone age grade assessment, in particular, the invention relates to a multi-classifier wrist bone grade recognition method based on height and age. Background technique [0002] Bone age is an ideal indicator for evaluating biological age and is widely used in fields such as medicine, sports and forensic identification. In the medical field, bone age is mainly used in the diagnosis and treatment of endocrine and growth and development diseases, as well as in surgical operations such as spine correction and lower limb balance. In the field of sports, bone age is mainly used to eliminate age fraud and standardize the order of competitions; to determine the developmental level of athletes and formulate scientific training methods; as an indicator for athlete selection, to select sports talents. In the field of forensic identification, bone age is mainly used to identify the age of criminal suspects or the de...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V10/764G06K9/62
CPCG06F18/2431
Inventor 毛科技丁维龙赵小敏万臧鑫陈立建
Owner 浙江康体汇科技有限公司
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