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A bone age detection method and device based on deep learning

A deep learning and bone age technology, applied in the fields of radiological diagnosis instruments, medical science, diagnosis, etc., can solve the problems that the accuracy cannot reach clinical use, and the real-time performance is not significantly better than the time.

Active Publication Date: 2020-06-30
ZHEJIANG UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing automated systems, either cannot reach the stage of clinical use in terms of accuracy, or are not significantly better than the time spent by doctors in terms of real-time research and judgment

Method used

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  • A bone age detection method and device based on deep learning
  • A bone age detection method and device based on deep learning
  • A bone age detection method and device based on deep learning

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Embodiment Construction

[0034] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0035] figure 1 is a structural diagram of a device 1 for detecting a subject's bone age according to an embodiment of the present invention. Such as figure 1 As shown, the device 1 includes an input unit 10 , an acquisition unit 11 , an extraction unit 12 , a correction unit 13 , a first determination unit 14 , and a second determination unit 15 .

[0036] figure 2 is a flowchart of a method for detecting a subject's bone age according to an embodiment of the present invention. In step S21, the input unit 10 inputs the X-ray picture of the subject's hand and the sex of the subject. Wherein, the subjects may be adolescents and children, for example, female children in this example. The input unit 10 will judge whether the input X-ray picture is an X-ray picture of the left hand, and if it is an X-ray picture of the left hand, it will go to step S...

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Abstract

The present invention provides a method and device for detecting the bone age of a subject based on deep learning. The method includes: an input step of inputting the X-ray picture of the subject's hand and the gender of the subject; Obtain multiple key points corresponding to each bone in the hand; the extraction step is to extract the respective initial pictures of some bones from the X-ray image; the correction step is to correct the initial pictures of each bone in the partial bones to obtain Respective corrected pictures of some bones; the first determining step is to determine the growth stage information of each bone in the partial bones, and to determine the growth stage information of the carpal bones when multiple bones do not include the carpal bones; the second determining step is to The bone age of the subject is determined based on the growth stage information of each bone in the partial skeleton, or based on the growth stage information of each bone in the partial skeleton and the growth stage information of the wrist bone.

Description

technical field [0001] The invention relates to a bone age detection method and device based on deep learning. Background technique [0002] "Bone age" is the abbreviation of skeletal age. It is the developmental age obtained by comparing the skeletal development level of adolescents and children with the bone development standard. It can more accurately reflect the maturity of the body than age, height, and weight, and more accurately reflect the individual. level of growth and maturity. [0003] Clinically, the biological age of children can be judged by detecting bone age, the development status of children can be evaluated by the difference between biological age and calendar age, the trend of sexual maturity of children can be understood, the adult height of children can be predicted, etc., and it is widely used in diseases that affect children's growth and development Treatment monitoring is of great help to the diagnosis of some pediatric endocrine diseases. [0004...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B6/00
CPCA61B6/505A61B6/5217
Inventor 傅君芬倪浩赖灿郑永升俞刚
Owner ZHEJIANG UNIV
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