Thyroid nodule ultrasound image segmentation method, device and system

A technology of thyroid nodules and ultrasound images, applied in image analysis, image data processing, neural learning methods, etc., can solve the problem of low accuracy of thyroid nodule image segmentation, and achieve the effect of improving segmentation accuracy and accuracy

Pending Publication Date: 2022-04-29
GUANGDONG SHUNDE IND DESIGN INST GUANGDONG SHUNDE INNOVATIVE DESIGN INST
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the existing technology still has the following defects: the network model in the prior art often only considers the local information of the ultrasound image of the thyroid nodule, resulting in a low accuracy for the segmentation of the thyroid nodule image

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  • Thyroid nodule ultrasound image segmentation method, device and system
  • Thyroid nodule ultrasound image segmentation method, device and system
  • Thyroid nodule ultrasound image segmentation method, device and system

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specific Embodiment 1

[0027] The embodiment of the present invention firstly describes a method for segmenting an ultrasound image of a thyroid nodule. figure 1 A flowchart of an embodiment of a method for segmenting an ultrasound image of a thyroid nodule according to the present invention is shown.

[0028] like figure 1 As shown, the method includes the following steps:

[0029] S1: Obtain a preset model training data set and an ultrasound image data set to be segmented.

[0030] In order to improve the segmentation accuracy of the thyroid nodule region in the ultrasound image, the embodiment of the present invention proposes to improve the existing semantic segmentation network Unet, and introduce a preset hierarchical cascade multi-head self-attention module (H -MHSA module) and modify the original pooling layer downsampling to a dual-branch downsampling method, and train the improved model, and then use the trained model to treat the segmented ultrasound image (for ease of description and u...

specific Embodiment 2

[0043] Furthermore, the embodiment of the present invention also describes a method for segmenting an ultrasound image of a thyroid nodule. figure 2 A flowchart showing another embodiment of a method for segmenting an ultrasound image of a thyroid nodule according to the present invention.

[0044] like figure 2 As shown, the method includes the following steps:

[0045] A1: Replace the downsampling method of the preset semantic segmentation network Unet with the two-branch downsampling method to obtain the first improved model.

[0046] Among them, the two-branch downsampling method means that one branch is downsampled through a typical 3x3 convolution with a step size of 2, and the other branch is downsampled through maximum pooling and combined with 1x1 convolution for channel transformation. The two branches The information of Add is fused by element-by-element summation, which can retain more context information. In one embodiment, the preset RelU activation function...

specific Embodiment 3

[0069] In addition to the above method, the embodiment of the present invention also describes a device for segmenting ultrasound images of thyroid nodules. image 3 A structural diagram of an embodiment of a device for segmenting an ultrasound image of a thyroid nodule according to the present invention is shown.

[0070] As shown in the figure, the segmentation device includes a data acquisition unit 11 , a model training unit 12 and a segmentation extraction unit 13 .

[0071] The data acquiring unit 11 is used to acquire preset model training data sets and ultrasound image data sets to be segmented.

[0072] The model training unit 12 is configured to train and evaluate the preset first visual segmentation model according to the model training data set, so as to obtain the second visual segmentation model. The first visual segmentation model is obtained by introducing a preset hierarchical cascaded multi-head self-attention module and modifying the original pooling layer ...

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Abstract

The invention discloses a thyroid nodule ultrasound image segmentation method, device and system. The segmentation device comprises a data acquisition unit, a model training unit and a segmentation extraction unit. The segmentation system comprises an image segmentation module and a data storage module. A preset first visual segmentation model obtained by introducing a preset hierarchical cascade multi-head self-attention module on the basis of a preset semantic segmentation network Unet is trained and evaluated to obtain a second visual segmentation model, and then a to-be-segmented ultrasonic image is segmented through the second visual segmentation model. According to the thyroid nodule ultrasound image segmentation method, the thyroid nodule ultrasound image segmentation device and the thyroid nodule ultrasound image segmentation system, the segmentation accuracy of the thyroid nodule image is improved.

Description

technical field [0001] The invention relates to the field of segmentation of ultrasound images of thyroid nodules, and relates to a segmentation method, device and system for ultrasound images of thyroid nodules. Background technique [0002] Thyroid nodule is an important endocrine organ of the human body, located in the front of the neck below the thyroid cartilage, which secretes thyroid hormones to regulate the body's metabolism. According to epidemiological studies, palpable thyroid nodules appear in 4%-7% of the population, and hypoechoic nodules with irregular borders are more likely to develop into malignant nodules. The incidence of malignant thyroid nodules is 0.1%-0.2%. The shape and borders of thyroid nodules are key features that distinguish benign from malignant nodules. Image segmentation is to classify each pixel in the picture. Accurate image segmentation has always been a difficult problem, especially in the field of medical image segmentation. Accurate ...

Claims

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Application Information

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IPC IPC(8): G06T7/11G06N3/04G06N3/08
CPCG06T7/11G06N3/08G06T2207/10132G06T2207/20081G06T2207/20084G06N3/045
Inventor 孙俊杰林晓明王爽王洋
Owner GUANGDONG SHUNDE IND DESIGN INST GUANGDONG SHUNDE INNOVATIVE DESIGN INST
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