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Automatic bone age identification system based on improved residual network

A network and residual technology, applied in the field of image processing and deep learning, can solve problems such as less data

Inactive Publication Date: 2018-04-20
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

However, due to the small amount of data in this model, only more than a thousand pieces of data, a model with a relatively simple network is used, and there is not enough data to support his results

Method used

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  • Automatic bone age identification system based on improved residual network
  • Automatic bone age identification system based on improved residual network
  • Automatic bone age identification system based on improved residual network

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Embodiment Construction

[0037] The present invention will be described in detail below in conjunction with various embodiments shown in the accompanying drawings

[0038] The object of the present invention is to propose a bone age recognition system based on an improved residual network for bone age detection using X-ray photos, which is cumbersome and subjective, and there is no automatic detection method with good performance.

[0039] In order to achieve the above purpose. The technical scheme adopted in the present invention is:

[0040] The invention discloses an automatic bone age identification system based on an improved residual network, and the specific implementation steps include:

[0041] (1) The samples in the sample library are divided into training samples and verification samples, and the pictures in the sample library are preprocessed to obtain the processed pictures.

[0042] (2) Construct a deep neural network, input the images processed in (1) into the network in batches, use ...

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Abstract

The invention discloses an automatic bone age identification system based on an improved residual network, and aims at solving the problem that an automatic deep learning processing means lacks in bone age detection via X ray photos domestically. The method comprises that data enhancement is carried out on a training sample, normalization is carried out, a bone age classification network based onthe improved residual error network is trained, 16 different slide windows are used during test, 16 classification results are predicted, and a classification of highest frequency is obtained.

Description

technical field [0001] The invention relates to the field of image processing and the field of deep learning, in particular to an automatic bone age recognition system based on an improved residual network. Background technique [0002] With the development of hardware equipment in recent years, image processing technology has become more and more mature, especially the development of deep learning in the past few years, which has accelerated the development of image processing technology. Deep learning has been used in various image processing fields, and has shown better results than traditional ones. Bone age detection is often used in medical clinics and athletes' qualification examinations. This technology uses X-rays to take pictures of wrist bones and palm bones in the medical and sports fields to evaluate the age of skeletal development. At present, the general method is to use manual film reading, which is cumbersome and subjective. [0003] At present, a bone age...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62A61B8/08
CPCA61B8/0875A61B8/5223G06F18/2415G06F18/214
Inventor 漆进胡顺达史鹏
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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