Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/153930
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dc.contributor.authorMukhmetov, Olzhasen_US
dc.contributor.authorMashekova, Aigerimen_US
dc.contributor.authorZhao, Yongen_US
dc.contributor.authorMidlenko, Annaen_US
dc.contributor.authorNg, Eddie Yin Kweeen_US
dc.contributor.authorFok, Sai Cheongen_US
dc.date.accessioned2022-01-07T06:18:05Z-
dc.date.available2022-01-07T06:18:05Z-
dc.date.issued2021-
dc.identifier.citationMukhmetov, 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/app11146565en_US
dc.identifier.issn2076-3417en_US
dc.identifier.urihttps://hdl.handle.net/10356/153930-
dc.description.abstractBackground: 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.en_US
dc.language.isoenen_US
dc.relation.ispartofApplied Sciencesen_US
dc.rights© 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/).en_US
dc.subjectEngineering::Mechanical engineeringen_US
dc.titlePatient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modellingen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.identifier.doi10.3390/app11146565-
dc.description.versionPublished versionen_US
dc.identifier.scopus2-s2.0-85111143392-
dc.identifier.issue14en_US
dc.identifier.volume11en_US
dc.identifier.spage6565en_US
dc.subject.keywordsFinite Element Modellingen_US
dc.subject.keywordsBreast Canceren_US
dc.description.acknowledgementThis 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.en_US
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