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

Diversity discrimination learning-based breast tumor recognition method

A recognition method, breast tumor technology, applied in the field of breast tumor recognition based on diversity discrimination learning, can solve the problems of low recognition accuracy of benign and malignant tumors, can not effectively solve the problem of low recognition accuracy of multi-morphic tumors, and achieve the effect of reducing the impact

Inactive Publication Date: 2018-11-30
JINAN INSPUR HIGH TECH TECH DEV CO LTD
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Because the traditional method has low accuracy in identifying benign and malignant tumors, it cannot effectively solve the problem of low accuracy in identifying polymorphic tumors

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
  • Diversity discrimination learning-based breast tumor recognition method
  • Diversity discrimination learning-based breast tumor recognition method
  • Diversity discrimination learning-based breast tumor recognition method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0020] A breast tumor identification method based on diversity discriminative learning. First, a diversity classification learning model is created to classify the diversity status of tumors, and then a discriminative learning model is created to classify tumors that are significantly different from normal tumors. Tumors are classified, and tumors are identified by the diversity classification learning model and the discriminative learning model.

[0021] The diversity classification learning model uses the convolutional neural network framework and plans to use Alexnet as the base diversity classification learning model, and the samples are divided into two types: normal tumors and abnormal tumors; Ultrasound images are labeled, and labeled as two types of images of normal tumors and abnormal tumors; the labeled images are input into Alexnet, and a diversity classification learning model is obtained by training.

[0022] The discriminative learning model is used to identify a...

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 diversity discrimination learning-based breast tumor recognition method. According to the method, a diversity classification learning model which is used for classifying diversity states of tumors is firstly created; a discriminative learning model which is used for classifying tumors greatly different from normal tumors is created; and a tumor is recognized through the diversity classification learning model and the discriminative learning model. Compared with the prior art, the diversity discrimination learning-based breast tumor recognition method is capable of effectively classifying diversity states of tumors so as to decrease influences, on performance, of diversities; normal tumors can be recognized by utilizing a traditional classification model; and abnormal tumors can be input into the discriminative learning model to be recognized, so that breast tumor can be correctly recognized and significance is provided for the early-stage auxiliary diagnosis of the breast tumor.

Description

technical field [0001] The invention relates to the field of medical image processing, in particular to a breast tumor identification method based on diversity discrimination learning. Background technique [0002] Breast cancer is a disease with a high mortality rate. The identification of benign and malignant breast tumors based on ultrasound images is an important tool for the auxiliary diagnosis of breast cancer. However, tumors have different morphologies, and even if they belong to the same category, they have many different characteristics. Due to the low accuracy of traditional methods in identifying benign and malignant tumors, it cannot effectively solve the problem of low identification accuracy of polymorphic tumors. SUMMARY OF THE INVENTION [0003] The technical task of the present invention is to provide a breast tumor identification method based on diversity discrimination learning. [0004] The technical task of the present invention is achieved in the f...

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 Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V2201/032G06N3/045G06F18/24G06F18/214
Inventor 袭肖明于治楼
Owner JINAN INSPUR HIGH TECH TECH DEV CO LTD
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