Intelligent Diagnosis of Breast Cancer with Thermograms using Convolutional Neural Networks

Nurduman Aidossov, Aigerim Mashekova, Yong Zhao, Vasilios Zarikas, Eddie Ng, Olzhas Mukhmetov

2022

Abstract

Breast cancer is a serious public health issue among women all over the world. The main methods of breast cancer diagnosis include ultrasound, mammography and Magnetic Resonance Imaging (MRI). However, the existing methods of diagnosis are not appropriate for regular mass screening in short intervals. On the other hand, there is one non-invasive and low-cost method for mass and regular screening which is the so-called thermography. Recent studies show rapid quality improvement of thermal cameras as well as distinct development of machine learning techniques that can be combined together to enhance the technology of breast cancer detection. Machine learning technologies can potentially be used to support the interpretation of thermal images and help physicians to automatically determine the locations and sizes of tumors, blood perfusion, and other patient-specific properties of breast tissues. In this study, we aim to develop CNN techniques for intelligent precision breast tumor diagnosis. The main innovation of our work is the use of breast thermograms from a multicenter database without preprocessing for binary classification. The results presented in this paper highlight the usefulness and efficiency of deep learning for standardized analysis of thermograms. It is found that the model developed can have an accuracy of 80.77%, sensitivity of 44.44 % and the specificity of 100%.

Paper Citation

in Harvard Style

Aidossov N., Mashekova A., Zhao Y., Zarikas V., Ng E. and Mukhmetov O. (2022). Intelligent Diagnosis of Breast Cancer with Thermograms using Convolutional Neural Networks. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-547-0, pages 598-604. DOI: 10.5220/0010920700003116

in Bibtex Style

@conference{icaart22,
author={Nurduman Aidossov and Aigerim Mashekova and Yong Zhao and Vasilios Zarikas and Eddie Ng and Olzhas Mukhmetov},
title={Intelligent Diagnosis of Breast Cancer with Thermograms using Convolutional Neural Networks},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2022},
pages={598-604},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010920700003116},
isbn={978-989-758-547-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Intelligent Diagnosis of Breast Cancer with Thermograms using Convolutional Neural Networks
SN - 978-989-758-547-0
AU - Aidossov N.
AU - Mashekova A.
AU - Zhao Y.
AU - Zarikas V.
AU - Ng E.
AU - Mukhmetov O.
PY - 2022
SP - 598
EP - 604
DO - 10.5220/0010920700003116