Hostname: page-component-5c6d5d7d68-wtssw Total loading time: 0 Render date: 2024-08-18T11:14:50.883Z Has data issue: false hasContentIssue false

A novel approach of high-resolution UWB microwave imaging system based on an improved 3D back-projection method for early-stage breast cancer detection applications

Published online by Cambridge University Press:  24 July 2020

M. Mehranpour
Affiliation:
Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin, Iran
S. Jarchi*
Affiliation:
Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin, Iran
A. Ghorbani
Affiliation:
Amirkabir University of Technology, Tehran, Iran
A. Keshtkar
Affiliation:
Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin, Iran
*
Author for correspondence: S. Jarchi, E-mail: s.jarchi@eng.ikiu.ac.ir

Abstract

In this paper, a novel approach of high-accuracy calibration (HAC) method is employed to improve the resolution of tumor detection within a fibro-glandular breast model, and also an improved 3D back-projection approach to scan each focal point inside of the breast is presented. For these purposes, a simulated hemispherical setup of a multi-static array with a modified UWB bowtie antenna is applied around the breast. The superiority of the proposed HAC method is that all-time delays of multi-static channel paths are taken into account at preprocessing of reflected signals, and therefore the time location of tumor response can be estimated accurately in the late stage of recorded signals. As a result, stronger signals are obtained to detect the location of the tumor with higher spatial accuracy. By using the improved 3D back-projection method, a better approximation of transmission channel paths based on Fermat's principle is achieved. A realistic breast model is proposed with two cases of single and twin spherical tumors. Then, to validate the efficiency of the proposed HAC method to detect the time-dependent tumor location, several scenarios are studied in the mentioned model. Quantitative metrics of successfully reconstructed tumor (with a small radius of 7 mm) images prove the ability of the proposed imaging method for early-stage breast cancer detection.

Type
Biomedical Applications
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Breast Cancer, Facts & Figures 2018–2019, Available at https://www.cancer.org.Google Scholar
Fear, EC, Meaney, PM and Stuchly, MA (2003) Microwaves for breast cancer detection? IEEE Potentials 22, 1218.Google Scholar
Shahzad, A (2018) Fast ultra wideband microwave imaging for early stage breast cancer detection. PhD diss.Google Scholar
Surowiec, AJ, Stuchly, SS, Barr, JR and Swarup, A (1988) Dielectric properties of breast carcinoma and the surrounding tissues. IEEE Transactions on Biomedical Engineering 35, 257263.CrossRefGoogle ScholarPubMed
Lazebnik, M, McCartney, L, Popovic, D, Watkins, CB, Lindstrom, MJ, Harter, J, Sewall, S, Magliocco, A, Booske, JH and Okoniewski, M (2007) A large-scale study of the ultrawideband microwave dielectric properties of normal breast tissue obtained from reduction surgeries. Physics in Medicine and Biology 52, 2637.CrossRefGoogle ScholarPubMed
Kwon, S, Son, S and Lee, K (2018) Experimental demonstration of in-place calibration for time domain microwave imaging system. Radio Science 53, 429439.CrossRefGoogle Scholar
Li, X and Hagness, SC (2001) A confocal microwave imaging algorithm for breast cancer detection. IEEE Microwave and Wireless Components Letters 11, 130132.Google Scholar
Been Lim, H, Thi Tuyet Nhung, N, Li, E and Duc Thang, N (2008) Confocal microwave imaging for breast cancer detection: delay-multiply-and-sum image reconstruction algorithm. IEEE Transactions on Biomedical Engineering 55, 16971704.CrossRefGoogle ScholarPubMed
Bond, EJ, Li, X, Hagness, SC and Van Veen, BD (2003) Microwave imaging via space-time beamforming for early detection of breast cancer. IEEE Transactions Antennas and Propagation 51, 16901705.CrossRefGoogle Scholar
Klemm, M, Craddock, IJ, Leendertz, JA, Preece, A and Benjamin, R (2008) Improved delay-and-sum beamforming algorithm for breast cancer detection. International Journal of Antennas and Propagation 2008, 19.Google Scholar
Conceicao, RC, Mohr, JJ and O'Halloran, M (2016) An introduction to microwave imaging for breast cancer detection. Springer Biomedical Engineering. eBook ISBN: 978-3-319-27866-7.Google Scholar
Yin, T, Ali, FH and Reyes-Aldasoro, CC (2015) A robust and artifact resistant algorithm of ultrawideband imaging system for breast cancer detection. IEEE Transactions on Biomedical Engineering 62, 15141525.Google Scholar
Xie, Y, Guo, B, Xu, L, Li, J and Stoica, P (2006) Multistatic adaptive microwave imaging for early breast cancer detection. IEEE Transactions on Biomedical Engineering 53, 16471657.CrossRefGoogle ScholarPubMed
Chen, Y, Craddock, IJ, Kosmas, P, Ghavami, M and Rapajic, P (2010) Multiple-input multiple-output radar for lesion classification in ultrawideband breast imaging. IEEE Journal of Selected Topics in Signal Processing 4, 187201.Google Scholar
Byrne, D and Craddock, I (2015) Time-domain wideband adaptive beamforming for radar breast imaging. IEEE Transactions on Antennas and Propagation 63, 17251735.Google Scholar
Meaney, PM, Fanning, MW, Li, Dun, Poplack, SP and Paulsen, KD (2000) A clinical prototype for active microwave imaging of the breast. IEEE Transactions on Microwave Theory and Techniques 48, 18411853.Google Scholar
Lai, JCY, Soh, CB, Gunawan, E, and Low, KS (2011) UWB Microwave imaging for breast cancer detection – experiments with heterogeneous breast phantoms. Progress in Electromagnetics Research M 16, 1929.CrossRefGoogle Scholar
Fear, E, Li, X, Hagness, S and Stuchly, M (2002) Confocal microwave imaging for breast cancer detection: localization of tumors in three dimensions. IEEE Transactions on Biomedical Engineering 49, 812822.CrossRefGoogle ScholarPubMed
Fear, E and Sill, J (2003) Preliminary investigations of tissue sensing adaptive radar for breast tumor detection. in Proceedings of the 25th Annual International Conference of the IEEE Engineering In Medicine and Biology Society, Sep. 2003, vol. 4, pp. 3787–3790.Google Scholar
O'Halloran, M, Jones, E and Glavin, M (2010) Quasi-multistatic MIST beamforming for the early detection of breast cancer. IEEE Transactions on Biomedical Engineering 57, 830840.CrossRefGoogle ScholarPubMed
Sill, J and Fear, E (2005) Tissue sensing adaptive radar for breast cancer detection – experimental investigation of simple tumor models.IEEE Transactions on Microwave Theory and Techniques 53, 33123319.CrossRefGoogle Scholar
Zhi, W and Chin, F (2006) Entropy-based time window for artifact removal in UWB imaging of breast cancer detection. Signal Processing Letters, IEEE 13, 585588.CrossRefGoogle Scholar
Elahi, MA, Shahzad, A, Glavin, M, Jones, E and O'Halloran, M (2014) Hybrid artifact removal for confocal microwave breast imaging. IEEE Antennas Wireless Propagation Letters 13, 149152.CrossRefGoogle Scholar
Elahi, MA, Shahzad, A, Glavin, M, Jones, E and O'Halloran, M (2017) Adaptive artifact removal for selective multistatic microwave breast imaging signals. Elsevier Biomedical Signal Processing and Control 34, 93100.CrossRefGoogle Scholar
Klemm, M, Leendertz, J, Gibbins, D, Craddock, I, Preece, A and Benjamin, R (2009) Microwave radar-based breast cancer detection: imaging in inhomogeneous breast phantoms. Antennas and Wireless Propagation Letters, IEEE 8, 13491352.CrossRefGoogle Scholar
Byrne, D, Mantalena, S and Craddock, IJ (2017) Compound radar approach for breast imaging. IEEE Transactions on Biomedical Engineering 64, 4051.CrossRefGoogle ScholarPubMed
Maskooki, A and Gunawan, E (2009) Frequency domain skin artifact removal method for ultrawideband breast cancer detection. Progress in Electromagnetics Research 98, 299314.Google Scholar
Schuster, A (1904) An introduction to the theory of optics: E. Arnold.Google Scholar
Klemm, M, Klemm, M, Craddock, IJ, Leendertz, JA, Preece, A and Benjamin, R (2009) Radar-based breast cancer detection using a hemispherical antenna array – experimental results. IEEE Transactions on Antennas and Propagation 57, 16921704.CrossRefGoogle Scholar
Wisconsin System, U. University of Wisconsin cross-disciplinary electromagnetics laboratory@ONLINE, Available at http://uwcem.ece.wisc.edu/phantomRepository.html (2020).Google Scholar
CST Microwave Studio. ver. 2019, CST, Framingham, MA, USA.Google Scholar
Lazebnik, M, Popovic, D, McCartney, L, Watkins, CB, Lindstrom, MJ, Harter, J, Sewall, S, Ogilvie, T, Magliocco, A, Breslin, TM, Temple, W, Mew, D, Booske, JH, Okoniewski, M, and Hagness, SC (2007) A large-scale study of the ultrawideband microwave dielectric properties of normal, benign and malignant breast tissues obtained from cancer surgeries. Physics in Medicine and Biology 52, 60936115.CrossRefGoogle ScholarPubMed
MATLAB. Matlab program@ONLINE, Available at http://www.mathworks.com/store?s_eid=ppc_29850095842&q=matlab (2018).Google Scholar
Morabito, AF (2016) Power synthesis of mask-constrained shaped beams through maximally-sparse planar arrays. Telkomnika (Telecommunication Computing Electronics and Control) 14, 12171219.CrossRefGoogle Scholar
Zhu, X, Zhao, Z, Wang, J, Song, J and Liu, QH (2013) Microwave-induced thermal acoustic tomography for breast tumor based on compressive sensing. IEEE Transactions on Biomedical Engineering 60, 12981307.Google ScholarPubMed
Jalilvand, M (2017) Application-specific broadband antennas for microwave medical imaging. eBook ISBN: 3731506645.Google Scholar
LaComb, JA and Mileski, PM (2009) Ultra wideband surface wave communication. Progress in Electromagnetics Research C 8, 95105.CrossRefGoogle Scholar
Sarafianou, M, Craddock, IJ, Henriksson, TNT, Klemm, M, Gibbins, DR, Preece, AW, Leendertz, J, and Benjamin, R (2013) Music processing for permittivity estimation in a delay-and-sum imaging system. in Proceedings of the 7th European Conference on Antennas and Propagation, pp. 839–842.Google Scholar
Dove, I (2014) Analysis of radio propagation inside the human body for in-body localization purposes. (M.Sc. Thesis.).Google Scholar
Martin, J and Crowley, JL (1995) Comparison of correlation techniques. in Proceedings of the International Conference on Intelligent Autonomous Systems, Karlsruhe, Germany, pp. 86–93.Google Scholar
Loughlin, DO, Oliveria, BL, Galvin, M, Jones, E and Halloran, MO (2019) Comparing radar based breast imaging algorithm performance with realistic patient-specific permittivity estimation. Journal of Imaging 5, 87.CrossRefGoogle Scholar