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Mammary gland molybdenum target AI auxiliary screening method

A mammography and screening technology, applied in mammography, neural learning methods, computer-aided medical procedures, etc., can solve the problems of low awareness of cancer health examination, difficult breast cancer screening, and lack of professional doctors.

Active Publication Date: 2020-09-25
CHENGDU GOLDISC UESTC MULTIMEDIA TECH
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AI Technical Summary

Problems solved by technology

On the one hand, this is due to the lack of public awareness of cancer health checks, and on the other hand, due to the lack of professional doctors, it is difficult to fully implement breast cancer screening at the grassroots level

Method used

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  • Mammary gland molybdenum target AI auxiliary screening method
  • Mammary gland molybdenum target AI auxiliary screening method
  • Mammary gland molybdenum target AI auxiliary screening method

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Embodiment

[0045] Such as figure 1 As shown, a breast mammography AI-assisted screening method includes the following steps:

[0046] Step S1: Obtain and input image data and non-image data; wherein, the image data includes left and right breast CC and MLO mammography images and breast tumor labels of the corresponding images, and supervised multi-task classification learning is performed;

[0047] Such as figure 2As shown, step S2: build a benign and malignant detection model; that is, use the multi-task classification learning in step S1 to simultaneously learn the benign and malignant classification tasks and the BI-RADS classification task, and extract the CNN features and non-image features of 4 images of each patient. Features, the previously extracted CNN features and non-image features are concatenated, input into the benign and malignant classifier to learn whether the patient has cancer, and at the same time input into the BI-RADS classifier to learn the BI-RADS level;

[00...

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Abstract

The invention discloses a mammary gland molybdenum target AI auxiliary screening method. The method comprises the following steps: S1, acquiring and inputting image data and non-image data; s2, constructing a benign and malignant detection model; and S3, constructing a lesion area positioning model. The invention develops an AI auxiliary detection algorithm for a mammary gland molybdenum target image from coarse to fine. Firstly, four high-resolution images of CC-position and MLO-position molybdenum target images of left and right breasts are acquired; the four high-resolution images are inputinto a multi-view breast molybdenum target benign and malignant classification model, benign and malignant conditions of each molybdenum target image are identified, and finally refined disease benign and malignant identification and positioning is performed on the breast molybdenum target image by using a Faster R-CNN disease detection model.

Description

technical field [0001] The invention belongs to the technical field of image data identification and processing, and in particular relates to an AI-assisted screening method for mammography. Background technique [0002] In recent years, the growth rate of the incidence of breast cancer in my country is 1-2 percentage points higher than that of high-incidence countries. According to the 2009 breast cancer incidence data released by the National Cancer Center and the Ministry of Health's Bureau of Disease Control and Prevention in 2012, the incidence of breast cancer in the national tumor registration area ranks first among female malignant tumors, and the incidence of female breast cancer (crude rate) is the highest in the country. The total is 42.55 / 100,000, 51.91 / 100,000 in cities, and 23.12 / 100,000 in rural areas. [0003] Compared with the United States, the five-year survival rate in my country is still relatively low. This is mainly due to the large population base in...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/73G06K9/62G06N3/04G06N3/08G16H30/20G16H50/30A61B6/00
CPCG06T7/0012G06T7/73G06N3/08G16H30/20G16H50/30A61B6/502A61B6/5294G06T2207/10116G06T2207/20081G06T2207/30068G06N3/045G06F18/24G06F18/214
Inventor 曲建明蒲立新刘欢欢曹旭
Owner CHENGDU GOLDISC UESTC MULTIMEDIA TECH
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