Research on the detection method of breast cancer deep convolutional neural network based on computer aid

Mengfan Li

doi:10.1109/IPEC51340.2021.9421338

Research on the detection method of breast cancer deep convolutional neural network based on computer aid

Mengfan Li^*

^*Corresponding author for this work

Xi'an Jiaotong-Liverpool University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

24 Citations (Scopus)

Abstract

Traditional breast cancer image classification methods require manual extraction of features from medical images, which not only require professional medical knowledge, but also have problems such as time-consuming and labor-intensive and difficulty in extracting high-quality features. Therefore, the paper proposes a computer-based feature fusion Convolutional neural network breast cancer image classification and detection method. The paper pre-trains two convolutional neural networks with different structures, and then uses the convolutional neural network to automatically extract the characteristics of features, fuse the features extracted from the two structures, and finally use the classifier classifies the fused features. The experimental results show that the accuracy of this method in the classification of breast cancer image data sets is 89%, and the classification accuracy of breast cancer images is significantly improved compared with traditional methods.

Original language	English
Title of host publication	Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	536-540
Number of pages	5
ISBN (Electronic)	9781728190181
DOIs	https://doi.org/10.1109/IPEC51340.2021.9421338
Publication status	Published - 14 Apr 2021
Externally published	Yes
Event	2nd IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021 - Dalian, China Duration: 14 Apr 2021 → 16 Apr 2021

Publication series

Name	Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021

Conference

Conference	2nd IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021
Country/Territory	China
City	Dalian
Period	14/04/21 → 16/04/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Breast cancer medical image
Breast cancer recognition
Computer-aided
Deep convolutional network
Deep learning network

Access to Document

10.1109/IPEC51340.2021.9421338

Cite this

Li, M. (2021). Research on the detection method of breast cancer deep convolutional neural network based on computer aid. In Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021 (pp. 536-540). Article 9421338 (Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPEC51340.2021.9421338

Li, Mengfan. / Research on the detection method of breast cancer deep convolutional neural network based on computer aid. Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 536-540 (Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021).

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title = "Research on the detection method of breast cancer deep convolutional neural network based on computer aid",

abstract = "Traditional breast cancer image classification methods require manual extraction of features from medical images, which not only require professional medical knowledge, but also have problems such as time-consuming and labor-intensive and difficulty in extracting high-quality features. Therefore, the paper proposes a computer-based feature fusion Convolutional neural network breast cancer image classification and detection method. The paper pre-trains two convolutional neural networks with different structures, and then uses the convolutional neural network to automatically extract the characteristics of features, fuse the features extracted from the two structures, and finally use the classifier classifies the fused features. The experimental results show that the accuracy of this method in the classification of breast cancer image data sets is 89\%, and the classification accuracy of breast cancer images is significantly improved compared with traditional methods. ",

keywords = "Breast cancer medical image, Breast cancer recognition, Computer-aided, Deep convolutional network, Deep learning network",

author = "Mengfan Li",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2nd IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021 ; Conference date: 14-04-2021 Through 16-04-2021",

year = "2021",

month = apr,

day = "14",

doi = "10.1109/IPEC51340.2021.9421338",

language = "English",

series = "Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "536--540",

booktitle = "Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021",

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Li, M 2021, Research on the detection method of breast cancer deep convolutional neural network based on computer aid. in Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021., 9421338, Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 536-540, 2nd IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021, Dalian, China, 14/04/21. https://doi.org/10.1109/IPEC51340.2021.9421338

Research on the detection method of breast cancer deep convolutional neural network based on computer aid. / Li, Mengfan.
Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 536-540 9421338 (Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Research on the detection method of breast cancer deep convolutional neural network based on computer aid

AU - Li, Mengfan

PY - 2021/4/14

Y1 - 2021/4/14

N2 - Traditional breast cancer image classification methods require manual extraction of features from medical images, which not only require professional medical knowledge, but also have problems such as time-consuming and labor-intensive and difficulty in extracting high-quality features. Therefore, the paper proposes a computer-based feature fusion Convolutional neural network breast cancer image classification and detection method. The paper pre-trains two convolutional neural networks with different structures, and then uses the convolutional neural network to automatically extract the characteristics of features, fuse the features extracted from the two structures, and finally use the classifier classifies the fused features. The experimental results show that the accuracy of this method in the classification of breast cancer image data sets is 89%, and the classification accuracy of breast cancer images is significantly improved compared with traditional methods.

AB - Traditional breast cancer image classification methods require manual extraction of features from medical images, which not only require professional medical knowledge, but also have problems such as time-consuming and labor-intensive and difficulty in extracting high-quality features. Therefore, the paper proposes a computer-based feature fusion Convolutional neural network breast cancer image classification and detection method. The paper pre-trains two convolutional neural networks with different structures, and then uses the convolutional neural network to automatically extract the characteristics of features, fuse the features extracted from the two structures, and finally use the classifier classifies the fused features. The experimental results show that the accuracy of this method in the classification of breast cancer image data sets is 89%, and the classification accuracy of breast cancer images is significantly improved compared with traditional methods.

KW - Breast cancer medical image

KW - Breast cancer recognition

KW - Computer-aided

KW - Deep convolutional network

KW - Deep learning network

UR - https://www.scopus.com/pages/publications/85106192052

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DO - 10.1109/IPEC51340.2021.9421338

M3 - Conference Proceeding

AN - SCOPUS:85106192052

T3 - Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021

SP - 536

EP - 540

BT - Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021

Y2 - 14 April 2021 through 16 April 2021

ER -

Li M. Research on the detection method of breast cancer deep convolutional neural network based on computer aid. In Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 536-540. 9421338. (Proceedings of IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021). doi: 10.1109/IPEC51340.2021.9421338

Research on the detection method of breast cancer deep convolutional neural network based on computer aid

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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