Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Thyroid nodule automatic identification model construction method, system and equipment

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: 2021-03-16
北京小白世纪网络科技有限公司
View PDF4 Cites 0 Cited by
  • 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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Thyroid nodule automatic identification model construction method, system and equipment
  • Thyroid nodule automatic identification model construction method, system and equipment
  • Thyroid nodule automatic identification model construction method, system and equipment

Examples

Experimental program
Comparison scheme
Effect test

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...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method, system and equipment for constructing a thyroid nodule automatic recognition model based on a convolutional neural network. The data set is input to ResNet, DenseNet, and / or ResNext to train the malignant probability of thyroid nodules to obtain the automatic recognition model of thyroid nodules; the test data set is used to test the automatic recognition model of thyroid nodules.

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(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
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com