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Ultra-wideband microwave breast tumor size prediction system based on long short-term memory

A long-short-term memory and breast tumor technology, applied in mammography, diagnostic recording/measurement, medical science, etc., can solve problems such as ignoring the correlation of time series signals

Active Publication Date: 2021-11-12
DONGHUA UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Traditional methods using a single state signal to classify or detect tumors ignore the correlation of time series signals

Method used

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  • Ultra-wideband microwave breast tumor size prediction system based on long short-term memory
  • Ultra-wideband microwave breast tumor size prediction system based on long short-term memory
  • Ultra-wideband microwave breast tumor size prediction system based on long short-term memory

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[0022] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0023] The present invention proposes a tumor size prediction framework based on LSTM recurrent neural network to estimate the size and growth trend of the tumor by considering the relationship between continuously acquired signals. In the prediction of tumor size data based on LSTM, not only the dependence between tumors can be captured, but also the long-term behavior of tumor growth can be learned, and the monitoring of brea...

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Abstract

The present invention provides an ultra-broadband microwave breast tumor size prediction system based on long-short-term memory, which uses the ultra-broadband microwave detection system to realize breast tumor size prediction based on long-short-term memory algorithm, including the following steps: according to the normal components in the breast (such as glands, fat, etc.) and the electromagnetic characteristics between tumors, build an ultra-broadband microwave breast tumor signal acquisition system; and then collect tumor sequence data at different times according to the tumor growth model. Then preprocess the data samples; then select the appropriate LSTM training parameters to establish the LSTM tumor prediction model; then put the processed data samples into the LSTM model for training; finally select the test samples, preprocess the test samples and input In the trained LSTM tumor model, according to the microwave data information of the tumor, the size of the tumor is detected and the growth trend of the tumor is predicted.

Description

technical field [0001] The present invention relates to a prediction system for estimating and monitoring breast tumor size using Long Short-Term Memory (LSTM) algorithm. Background technique [0002] According to reports, the incidence of breast cancer in American white women is about 13.1%, while the incidence of breast cancer in Asian women is about 4% to 7%. The average 5-year survival rate of breast cancer in the United States is 90%, but only 73.1% in China. Although the incidence of breast cancer in European and American countries is high, the mortality rate is very low. The main reason for this difference is, on the one hand, the higher level of medical care in many developed countries. Another aspect is that in the vast majority of cases, breast cancer patients are diagnosed at an early stage. Due to the preventable nature of breast cancer, diagnosis through frequent monitoring can improve the survival rate of cancer patients. Current breast cancer screening usin...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/0507A61B5/00G06N3/04
CPCA61B5/0507A61B5/4312A61B5/7275G06N3/044G06N3/045
Inventor 吴怡之朱海瑞
Owner DONGHUA UNIV
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