Thyroid nodule automatic identification model construction method, system and device

A technology for automatic identification of thyroid nodules, applied in the field of artificial intelligence, to achieve the effect of improving the effect of automatic identification

Active Publication Date: 2020-08-28
北京小白世纪网络科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, the work of thyroid automatic identification needs further research

Method used

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  • Thyroid nodule automatic identification model construction method, system and device
  • Thyroid nodule automatic identification model construction method, system and device
  • Thyroid nodule automatic identification model construction method, system and device

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Embodiment 1

[0068] An embodiment of the present invention provides a convolutional neural network-based automatic identification model building equipment for thyroid nodules, such as Figure 5 As shown, it includes: a memory 50, a processor 52, and a computer program stored on the memory 50 and operable on the processor 52. When the computer program is executed by the processor 52, the following method steps are implemented:

[0069] Step 101, data denoising is performed on the thyroid ultrasound image, and a training data set and a test data set are obtained; Step 101 specifically includes: performing grayscale processing on the thyroid ultrasound image to obtain a binarized image; on the basis of the binarized image , to carry out the image opening operation, that is, to corrode the image first and then expand the image to complete the data denoising of the ultrasound image of the thyroid gland.

[0070] It should be noted that, in the embodiment of the present invention, after the trai...

Embodiment 2

[0083] An embodiment of the present invention provides a computer-readable storage medium, where a program for realizing information transmission is stored on the computer-readable storage medium, and when the program is executed by the processor 52, the following method steps are implemented:

[0084] Step 101, data denoising is performed on the thyroid ultrasound image, and a training data set and a test data set are obtained; Step 101 specifically includes: performing grayscale processing on the thyroid ultrasound image to obtain a binarized image; on the basis of the binarized image , to carry out the image opening operation, that is, to corrode the image first and then expand the image to complete the data denoising of the ultrasound image of the thyroid gland.

[0085] It should be noted that, in the embodiment of the present invention, after the training data set is obtained, the training data set can be enhanced offline using cycle-GAN based on the generative confrontat...

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Abstract

The invention discloses a thyroid nodule automatic identification model construction method, system and device based on a convolutional neural network, and the thyroid nodule automatic identificationmodel construction method comprises the steps: carrying out the data noise reduction of a thyroid ultrasonic image, and obtaining a training data set and a test data set; inputting the training data set into ResNet, DenseNet, and/or ResNext to carry out thyroid nodule malignant probability training to obtain a thyroid nodule automatic identification model; and testing the thyroid nodule automaticidentification model by adopting the test data set.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a method, system and equipment for constructing a model for automatic recognition of thyroid nodules based on a convolutional neural network. Background technique [0002] The incidence of thyroid cancer has been increasing globally over the past two decades. The prevalence of thyroid cancer in men is three times that of women, and in China, thyroid cancer has become one of the most common cancers among women in their 30s. Ultrasound is the main means of screening for thyroid cancer. The quality of the detection results is usually judged by the ultrasound doctor based on experience. Therefore, the detection of benign and malignant thyroid nodules depends on the level of the doctor. According to the Reporting and Data System (TI-RADS) guidelines, thyroid cancer is divided into five different time stages I-V. Similarly, thyroid cancer can be divided into fo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06N3/04G06N3/08
CPCG06T7/0012G06N3/08G06T2207/10132G06T2207/20081G06T2207/20084G06T2207/30096G06N3/045
Inventor 杜强黄丹郭雨晨聂方兴张兴唐超
Owner 北京小白世纪网络科技有限公司
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