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Hand bone X-ray film bone age evaluation method based on heterogeneous data fusion network

A technology that integrates networks and heterogeneous data. It is applied in image data processing, biological neural network models, and neural architectures. It can solve problems such as difficulty, low efficiency, and low precision, and achieve high speed, high efficiency, and improved evaluation results. Effect

Active Publication Date: 2019-11-26
浙江飞图影像科技有限公司
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Problems solved by technology

[0005] In order to overcome the difficulties, low efficiency and low precision of existing bone age assessment methods, the present invention proposes a hand bone X-ray bone age assessment method based on heterogeneous data fusion network, which realizes the hand bone X-ray film bone age assessment method. Automatic analysis can effectively obtain accurate bone age assessment values

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  • Hand bone X-ray film bone age evaluation method based on heterogeneous data fusion network
  • Hand bone X-ray film bone age evaluation method based on heterogeneous data fusion network
  • Hand bone X-ray film bone age evaluation method based on heterogeneous data fusion network

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example

[0110] Example: X-ray of hand bones used in this case. There are 5286 samples of hand bone X-ray films, including 2731 cases of male hand bone X-ray films with text information and 2555 cases of female hand bone X-ray films with text information. 683 samples and 639 samples were selected from the male and female samples as the test set, and the remaining 2048 male samples and 1916 female samples were used as the test set. The following describes the training and testing process of the hand bone X-ray film model in detail.

[0111] Step 1, remove noise from hand bone X-ray film.

[0112] Step 1.1: image binarization;

[0113] Step 1.2: Erosion and dilation, filling the black area in the hand bone area;

[0114] Step 1.3: Contour detection, extracting the contour of the wrist bone;

[0115] Step 1.4: Customize the contour length threshold to remove redundant information at the wrist of the wrist bone.

[0116] Step 2, the construction and training of the neural network, the...

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Abstract

A hand bone X-ray film bone age evaluation method based on a heterogeneous data fusion network comprises: 1, preprocessing an X-ray film image, and extracting a wrist bone part in the image; step 2, constructing a convolutional neural network to extract image features; 3, constructing a text feature extraction model; 4, constructing a fusion layer, and combining the image features and the text features; step 5, model training: after sufficient convergence, storing and exporting a model structure and weight parameters; and performing bone age evaluation on the hand bone X-ray film by using thefusion network obtained by training. According to the invention, the accurate bone age can be obtained by analyzing the hand bone X-ray film by using the text information and the X-ray film image information.

Description

technical field [0001] The present invention relates to the fields of medical image analysis and machine learning, in particular to a bone age assessment method applied to X-ray films of hand bones, which belongs to the field of medical image analysis based on deep learning. Background technique [0002] During a child's development, bones change in size and shape. Therefore, discrepancies between a child's skeletal age and chronological age can reflect developmental problems. And as an important indicator of growth and development, skeletal age plays an important role in the fields of medicine, sports, etc., especially in the clinical management of adolescent scoliosis and other patients, bone maturity analysis is performed to understand its growth Peak and rest periods are critical in determining clinical observation intervals and timing the initiation and termination of supportive therapy. However, due to the large number of bone fragments in the wrist, the large amount...

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Application Information

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IPC IPC(8): G06T7/00G06T7/12G06T5/30G06T7/13G06K9/62G06N3/04
CPCG06T7/0012G06T7/12G06T5/30G06T7/13G06T2207/10116G06T2207/30008G06N3/045G06F18/253
Inventor 郝鹏翼叶涛涛吴福理丁维龙
Owner 浙江飞图影像科技有限公司
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