Patient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modelling
Background: Mammography is the preferred method for the diagnosis of breast cancer. However, this diagnostic technique fails to detect tumors of small sizes, and it does not work well for younger patients with high breast tissue density. Methods: This paper proposes a novel tool for the early detect...
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sg-ntu-dr.10356-1539302022-01-07T06:18:05Z Patient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modelling Mukhmetov, Olzhas Mashekova, Aigerim Zhao, Yong Midlenko, Anna Ng, Eddie Yin Kwee Fok, Sai Cheong School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Finite Element Modelling Breast Cancer Background: Mammography is the preferred method for the diagnosis of breast cancer. However, this diagnostic technique fails to detect tumors of small sizes, and it does not work well for younger patients with high breast tissue density. Methods: This paper proposes a novel tool for the early detection of breast cancer, which is patient-specific, non-invasive, inexpensive, and has potential in terms of accuracy compared with existing techniques. The main principle of this method is based on the use of temperature contours from breast skin surfaces through thermography, and inverse thermal modeling based on Finite Element Analysis (FEA) and a Genetic Algorithm (GA)-based optimization tool to estimate the depths and sizes of tumors as well as patient/breast-specific tissue properties. Results: The study was conducted by using a 3D geometry of patients’ breasts and their temperature contours, which were clinically collected using a 3D scanner and a thermal imaging infrared (IR) camera. Conclusion: The results showed that the combination of 3D breast geometries, thermal images, and inverse thermal modeling is capable of estimating patient/breast-specific breast tissue and physiological properties such as gland and fat contents, tissue density, thermal conductivity, specific heat, and blood perfusion rate, based on a multilayer model consisting of gland and fat. Moreover, this tool was able to calculate the depth and size of the tumor, which was validated by the doctor’s diagnosis. Published version This research was funded by Ministry of Education and Science of the Republic of Kazakhstan, AP08857347 (“Application of artificial intelligence to complement thermography for breast cancer prediction”). The APC was funded by Ministry of Education and Science of the Republic of Kazakhstan. 2022-01-07T06:18:05Z 2022-01-07T06:18:05Z 2021 Journal Article Mukhmetov, O., Mashekova, A., Zhao, Y., Midlenko, A., Ng, E. Y. K. & Fok, S. C. (2021). Patient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modelling. Applied Sciences, 11(14), 6565-. https://dx.doi.org/10.3390/app11146565 2076-3417 https://hdl.handle.net/10356/153930 10.3390/app11146565 2-s2.0-85111143392 14 11 6565 en Applied Sciences © 2021 The Author(s). Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). application/pdf |
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Engineering::Mechanical engineering Finite Element Modelling Breast Cancer Mukhmetov, Olzhas Mashekova, Aigerim Zhao, Yong Midlenko, Anna Ng, Eddie Yin Kwee Fok, Sai Cheong Patient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modelling |
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Background: Mammography is the preferred method for the diagnosis of breast cancer. However, this diagnostic technique fails to detect tumors of small sizes, and it does not work well for younger patients with high breast tissue density. Methods: This paper proposes a novel tool for the early detection of breast cancer, which is patient-specific, non-invasive, inexpensive, and has potential in terms of accuracy compared with existing techniques. The main principle of this method is based on the use of temperature contours from breast skin surfaces through thermography, and inverse thermal modeling based on Finite Element Analysis (FEA) and a Genetic Algorithm (GA)-based optimization tool to estimate the depths and sizes of tumors as well as patient/breast-specific tissue properties. Results: The study was conducted by using a 3D geometry of patients’ breasts and their temperature contours, which were clinically collected using a 3D scanner and a thermal imaging infrared (IR) camera. Conclusion: The results showed that the combination of 3D breast geometries, thermal images, and inverse thermal modeling is capable of estimating patient/breast-specific breast tissue and physiological properties such as gland and fat contents, tissue density, thermal conductivity, specific heat, and blood perfusion rate, based on a multilayer model consisting of gland and fat. Moreover, this tool was able to calculate the depth and size of the tumor, which was validated by the doctor’s diagnosis. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Mukhmetov, Olzhas Mashekova, Aigerim Zhao, Yong Midlenko, Anna Ng, Eddie Yin Kwee Fok, Sai Cheong |
format |
Article |
author |
Mukhmetov, Olzhas Mashekova, Aigerim Zhao, Yong Midlenko, Anna Ng, Eddie Yin Kwee Fok, Sai Cheong |
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Mukhmetov, Olzhas |
title |
Patient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modelling |
title_short |
Patient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modelling |
title_full |
Patient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modelling |
title_fullStr |
Patient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modelling |
title_full_unstemmed |
Patient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modelling |
title_sort |
patient/breast-specific detection of breast tumor based on patients’ thermograms, 3d breast scans, and reverse thermal modelling |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/153930 |
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1722355322662682624 |