Vol. 84
Latest Volume
All Volumes
PIERM 137 [2026] PIERM 136 [2025] PIERM 135 [2025] PIERM 134 [2025] PIERM 133 [2025] PIERM 132 [2025] PIERM 131 [2025] PIERM 130 [2024] PIERM 129 [2024] PIERM 128 [2024] PIERM 127 [2024] PIERM 126 [2024] PIERM 125 [2024] PIERM 124 [2024] PIERM 123 [2024] PIERM 122 [2023] PIERM 121 [2023] PIERM 120 [2023] PIERM 119 [2023] PIERM 118 [2023] PIERM 117 [2023] PIERM 116 [2023] PIERM 115 [2023] PIERM 114 [2022] PIERM 113 [2022] PIERM 112 [2022] PIERM 111 [2022] PIERM 110 [2022] PIERM 109 [2022] PIERM 108 [2022] PIERM 107 [2022] PIERM 106 [2021] PIERM 105 [2021] PIERM 104 [2021] PIERM 103 [2021] PIERM 102 [2021] PIERM 101 [2021] PIERM 100 [2021] PIERM 99 [2021] PIERM 98 [2020] PIERM 97 [2020] PIERM 96 [2020] PIERM 95 [2020] PIERM 94 [2020] PIERM 93 [2020] PIERM 92 [2020] PIERM 91 [2020] PIERM 90 [2020] PIERM 89 [2020] PIERM 88 [2020] PIERM 87 [2019] PIERM 86 [2019] PIERM 85 [2019] PIERM 84 [2019] PIERM 83 [2019] PIERM 82 [2019] PIERM 81 [2019] PIERM 80 [2019] PIERM 79 [2019] PIERM 78 [2019] PIERM 77 [2019] PIERM 76 [2018] PIERM 75 [2018] PIERM 74 [2018] PIERM 73 [2018] PIERM 72 [2018] PIERM 71 [2018] PIERM 70 [2018] PIERM 69 [2018] PIERM 68 [2018] PIERM 67 [2018] PIERM 66 [2018] PIERM 65 [2018] PIERM 64 [2018] PIERM 63 [2018] PIERM 62 [2017] PIERM 61 [2017] PIERM 60 [2017] PIERM 59 [2017] PIERM 58 [2017] PIERM 57 [2017] PIERM 56 [2017] PIERM 55 [2017] PIERM 54 [2017] PIERM 53 [2017] PIERM 52 [2016] PIERM 51 [2016] PIERM 50 [2016] PIERM 49 [2016] PIERM 48 [2016] PIERM 47 [2016] PIERM 46 [2016] PIERM 45 [2016] PIERM 44 [2015] PIERM 43 [2015] PIERM 42 [2015] PIERM 41 [2015] PIERM 40 [2014] PIERM 39 [2014] PIERM 38 [2014] PIERM 37 [2014] PIERM 36 [2014] PIERM 35 [2014] PIERM 34 [2014] PIERM 33 [2013] PIERM 32 [2013] PIERM 31 [2013] PIERM 30 [2013] PIERM 29 [2013] PIERM 28 [2013] PIERM 27 [2012] PIERM 26 [2012] PIERM 25 [2012] PIERM 24 [2012] PIERM 23 [2012] PIERM 22 [2012] PIERM 21 [2011] PIERM 20 [2011] PIERM 19 [2011] PIERM 18 [2011] PIERM 17 [2011] PIERM 16 [2011] PIERM 14 [2010] PIERM 13 [2010] PIERM 12 [2010] PIERM 11 [2010] PIERM 10 [2009] PIERM 9 [2009] PIERM 8 [2009] PIERM 7 [2009] PIERM 6 [2009] PIERM 5 [2008] PIERM 4 [2008] PIERM 3 [2008] PIERM 2 [2008] PIERM 1 [2008]
2019-08-29
Electrically Small Magnetic Probe with PCA for Near-Field Microwave Breast Tumors Detection
By
Progress In Electromagnetics Research M, Vol. 84, 177-186, 2019
Abstract
In this paper, an electrically small magnetic probe combined with principal components analysis (PCA) technique for microwave breast cancer detection is presented. The proposed magnetic probe is designed as an electrically small square loop antenna integrated with a matching network operating at 528 MHz. The concept of the proposed microwave detection is based on the shift in the resonance frequency of the near-field magnetic probe due to the presence of a tumor. The proposed magnetic probe is highly sensitive in detecting any changes or abnormality in the dielectric properties of the female breast tissues. Detecting the existence of the breast tumors is expected by estimating the variations in the scattering parameters of the probe's response. The PCA is a feature extraction technique applied to accentuate the variance in the sensor responses for both healthy and tumorous cases. It is shown that when a numerical realistic breast phantom with and without tumor cells is placed close to the magnetic probe in the near-field region, the probe is capable of distinguishing between healthy and tumorous tissues. In addition, the probe can identify tumors with various sizes placed in a specific location within the breast. As a proof of concept, the magnetic probe was fabricated and used to detect a 9 mm metallic sphere buried at three different locations inside a lump of chicken meat, mimicking both normal and tumorous breast tissues, respectively. The CST numerical simulations and experimental results demonstrate that the presented technique is an emerging modality for detecting breast tumors through an inexpensive and portable way.
Citation
Maged A. Aldhaeebi, Thamer S. Almoneef, Hussein Attia, and Omar M. Ramahi, "Electrically Small Magnetic Probe with PCA for Near-Field Microwave Breast Tumors Detection," Progress In Electromagnetics Research M, Vol. 84, 177-186, 2019.
doi:10.2528/PIERM19061303
References

1. Society, A. C., "Cancer facts and figures 2019 @ONLINE,", [Online]. Available: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-andstatistics/annual-cancer-facts-and-figures/2019/cancer-facts-and-figures-2019.pdf, 2019.
doi:10.1109/TEMC.2019.2896519        Google Scholar

2. Attaran, A., W. B. Handler, and B. A. Chronik, "2 mm radius loop antenna and linear active balun for near field measurement of magnetic field in MRI-conditional testing of medical devices," IEEE Transactions on Electromagnetic Compatibility, 1-8, 2019.
doi:10.1109/ICEAA.2017.8065655        Google Scholar

3. Radder, J., M. Woo, P. Van de Moortele, G. Metzger, A. Ertürk, J. Strupp, K. Ugurbil, and G. Adriany, "Optimization and simulation of a 16-channel loop and dipole array for head MRI applications at 10.5 tesla," 2017 International Conference on Electromagnetics in Advanced Applications (ICEAA), 1828-1831, Sep. 2017.
doi:10.3390/s17071572        Google Scholar

4. Wang, L., "Early diagnosis of breast cancer," Sensors, Vol. 17, No. 7, 1572, 2017.
doi:10.1049/iet-map.2017.0599        Google Scholar

5. Obermeier, R. and J. A. Martinez-Lorenzo, "Compressive sensing unmixing algorithm for breast cancer detection," IET Microwaves, Antennas & Propagation, Vol. 12, No. 4, 533-541, 2018.
doi:10.1109/TBME.2018.2807799        Google Scholar

6. Yousefnia, M., A. Ebrahimzadeh, M. Dehmollaian, and A. Madannejad, "A time-reversal imaging system for breast screening: Theory and initial phantom results," IEEE Transactions on Biomedical Engineering, Vol. 65, No. 11, 2542-2551, 2018.
doi:10.1007/978-3-319-27866-7        Google Scholar

7. Conceição, R. C., J. J. Mohr, and M. O'Halloran, An Introduction to Microwave Imaging for Breast Cancer Detection, Springer, 2016.
doi:10.1109/6668.990683

8. Fear, E. C., S. C. Hagness, P. M. Meaney, M. Okoniewski, and M. A. Stuchly, "Enhancing breast tumor detection with near-field imaging," IEEE Microwave magazine, Vol. 3, No. 1, 48-56, 2002.
doi:10.1109/22.883861        Google Scholar

9. Meaney, P. M., M. W. Fanning, D. Li, S. P. Poplack, and K. D. Paulsen, "A clinical prototype for active microwave imaging of the breast," IEEE Transactions on Microwave Theory and Techniques, Vol. 48, No. 11, 1841-1853, 2000.
doi:10.1163/156939304774113089        Google Scholar

10. Caorsi, S., M. Donelli, A. Lommi, and A. Massa, "Location and imaging of two-dimensional scatterers by using a particle swarm algorithm," Journal of Electromagnetic Waves and Applications, Vol. 18, No. 4, 481-494, 2004.
doi:10.2528/PIERM11040903        Google Scholar

11. Donelli, M., I. J. Craddock, D. Gibbins, and M. Sarafianou, "A three-dimensional time domain microwave imaging method for breast cancer detection based on an evolutionary algorithm," Progress In Electromagnetics Research, Vol. 18, 179-195, 2011.
doi:10.4218/etrij.10.0109.0626        Google Scholar

12. Son, S.-H., N. Simonov, H.-J. Kim, J.-M. Lee, and S.-I. Jeon, "Preclinical prototype development of a microwave tomography system for breast cancer detection," ETRI Journal, Vol. 32, No. 6, 901-910, 2010.        Google Scholar

13. Bridges, J. E., "Non-invasive system for breast cancer detection,", US Patent 5,704, 355, Jan. 6, 1998.
doi:10.1109/TBME.2002.800759        Google Scholar

14. Fear, E. C., X. Li, S. C. Hagness, and M. A. Stuchly, "Confocal microwave imaging for breast cancer detection: Localization of tumors in three dimensions," IEEE Transactions on Biomedical Engineering, Vol. 49, No. 8, 812-822, 2002.
doi:10.2528/PIERM11061206        Google Scholar

15. Donelli, M., "A rescue radar system for the detection of victims trapped under rubble based on the independent component analysis algorithm," Progress In Electromagnetics Research, Vol. 19, 173-181, 2011.
doi:10.3390/s18020655        Google Scholar

16. Wang, L., "Microwave sensors for breast cancer detection," Sensors, Vol. 18, No. 2, 655, 2018.        Google Scholar

17. Klemm, M., I. Craddock, J. Leendertz, A. Preece, and R. Benjamin, "Experimental and clinical results of breast cancer detection using uwb microwave radar," Antennas and Propagation Society International Symposium, 2008. AP-S 2008. IEEE, 1-4, 2008.
doi:10.1109/RBME.2011.2169780        Google Scholar

18. Hassan, A. M. and M. El-Shenawee, "Review of electromagnetic techniques for breast cancer detection," IEEE Reviews in Biomedical Engineering, Vol. 4, 103-118, 2011.
doi:10.1038/s41598-018-31046-9        Google Scholar

19. Aldhaeebi, M. A., T. S. Almoneef, A. Ali, Z. Ren, and O. M. Ramahi, "Near field breast tumor detection using ultra-narrow band probe with machine learning techniques," Scientific Reports, Vol. 8, No. 1, 12607, 2018.        Google Scholar

20. Bourqui, J., J. M. Sill, and E. C. Fear, "A prototype system for measuring microwave frequency reflections from the breast," Journal of Biomedical Imaging, Vol. 2012, 9, 2012.        Google Scholar

21. Gazhonova, V., 3D Automated Breast Volume Sonography: A Practical Guide, Springer, 2016.
doi:10.1016/j.mri.2012.10.022

22. Chen, J.-H., S. Chan, D.-C. Yeh, P. T. Fwu, M. Lin, and M.-Y. Su, "Response of bilateral breasts to the endogenous hormonal uctuation in a menstrual cycle evaluated using 3d mri," Magnetic Resonance Imaging, Vol. 31, No. 4, 538-544, 2013.        Google Scholar

23. CST "Computer simulation technology. cst computer simulation technology ag@ONLINE,", [Online]. Available: http://www.CST.com, Sep. 2017.        Google Scholar

24. UWCEM "Breast phantom repository@ONLINE,", [Online]. Available: http://uwcem.ece.wisc.edu/phantomRepository.html, Aug. 2017.        Google Scholar

25. Zastrow, E., S. Davis, M. Lazebnik, F. Kelcz, B. van Veem, and S. Hagness, "Database of 3D grid-based numerical breast phantoms for use in computational electromagnetics simulations,", [Online]. Available: https://uwcem.ece.wisc.edu/MRIdatabase/InstructionManual.pdf, 2008.
doi:10.1109/TBME.2008.2002130        Google Scholar

26. Zastrow, E., S. K. Davis, M. Lazebnik, F. Kelcz, B. D. Van Veen, and S. C. Hagness, "Development of anatomically realistic numerical breast phantoms with accurate dielectric properties for modeling microwave interactions with the human breast," IEEE Transactions on Biomedical Engineering, Vol. 55, No. 12, 2792-2800, 2008.
doi:10.1088/0031-9155/52/20/002        Google Scholar

27. Lazebnik, M., D. Popovic, L. McCartney, C. B. Watkins, M. J. Lindstrom, J. Harter, S. Sewall, T. Ogilvie, A. Magliocco, T. M. Breslin, et al. "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, Vol. 52, No. 20, 6093, 2007.        Google Scholar

28. Richardson, M., "Principal component analysis,", URL: http://people.maths.ox.ac.uk/richardsonm/SignalProcPCA.pdf (last access: 3.5. 2013), Aleš Hladnik Dr., Ass. Prof., Chair of Information and Graphic Arts Technology, Faculty of Natural Sciences and Engineering, University of Ljubljana, Slovenia, ales.hladnik@ntf. uni-lj.si, 2009.
doi:10.1002/wics.101        Google Scholar

29. Abdi, H. and L. J. Williams, "Principal component analysis," Wiley Interdisciplinary Reviews: Computational Statistics, Vol. 2, No. 4, 433-459, 2010.
doi:10.1098/rsta.2015.0202        Google Scholar

30. Jolliffe, I. T. and J. Cadima, "Principal component analysis: A review and recent developments," Phil. Trans. R. Soc. A, Vol. 374, No. 2065, 20150202, 2016.        Google Scholar