Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/153930
Title: Patient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modelling
Authors: Mukhmetov, Olzhas
Mashekova, Aigerim
Zhao, Yong
Midlenko, Anna
Ng, Eddie Yin Kwee
Fok, Sai Cheong
Keywords: Engineering::Mechanical engineering
Issue Date: 2021
Source: 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
Journal: Applied Sciences
Abstract: 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.
URI: https://hdl.handle.net/10356/153930
ISSN: 2076-3417
DOI: 10.3390/app11146565
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/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

Files in This Item:
File Description SizeFormat 
applsci-11-06565.pdf7.8 MBAdobe PDFView/Open

Page view(s)

20
Updated on May 20, 2022

Download(s)

6
Updated on May 20, 2022

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.