A breast cancer diagnose application using deep learning technology

Qing Hao; Guankai Sang; Wenqing Zhang

doi:10.1117/12.2622896

1 December 2021 A breast cancer diagnose application using deep learning technology

Qing Hao, Guankai Sang, Wenqing Zhang

Proceedings Volume 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering; 120791K (2021) https://doi.org/10.1117/12.2622896
Event: 2nd IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 2021, Xi'an, China

Abstract

Breast cancer is a cancer which has the highest morbidity in women worldwide. Modern medicine uses imaging methods to analyze pathological images, which may cause the human error, and consume resources and manpower. Deep learning can help people and doctors to detect breast cancer, treat it better. This paper developed a breast cancer diagnosis system based on the Convolutional Neural Networks (CNN). We proposed a convolutional model consists of two convolutional layers and pooling layers. The Breast Cancer Histopathology Image Classification (BreaKHis) dataset was used to contain benign and malignant two classes. BCE loss was used as the loss function during our training process. The learning rate, optimizer, training epochs are 0.001, Adam and 11, respectively. In addition, we also developed a breast cancer diagnosis application using the Flask, which the users can use to detect breast cancer online and know where has cancerous by putting red boxes. Experimental results indicate that our cancer diagnosis system can provide good feedback to breast cancer patients.

Citation Download Citation

Qing Hao, Guankai Sang, and Wenqing Zhang "A breast cancer diagnose application using deep learning technology", Proc. SPIE 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 120791K (1 December 2021); https://doi.org/10.1117/12.2622896

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Breast cancer

Cancer

Tumor growth modeling

RGB color model

Breast

Diagnostics

Biopsy

Show All Keywords

Keywords/Phrases

Search In:

Publication Years