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2013-12-16
Investigation of Classifiers for Tumor Detection with an Experimental Time-Domain Breast Screening System
By
Progress In Electromagnetics Research, Vol. 144, 45-57, 2014
Abstract
In this work we examine, for the first time, the use of classification algorithms for early-stage tumor detection with an experimental time-domain microwave breast screening system. The experimental system contains a 16-element antenna array, and testing is done on breast phantoms that mimic breast tissue dielectric properties. We obtain experimental data from multiple breast phantoms with two possible tumor locations. In this work, we investigate a method for detecting the tumors within the breast but without the usual complexity inherent to image-generation methods, and confirm its feasibility on experimental data. The proposed method uses machine learning techniques, namely Support Vector Machines (SVM) and Linear Discriminant Analysis (LDA), to determine whether the current breast being scanned is tumor-free. Our results show that both SVM and LDA methods have promise as algorithms supporting early breast cancer microwave screening.
Citation
Adam Santorelli, Emily Porter, Evgeny Kirshin, Yi Jun Liu, and Milica Popović, "Investigation of Classifiers for Tumor Detection with an Experimental Time-Domain Breast Screening System," Progress In Electromagnetics Research, Vol. 144, 45-57, 2014.
doi:10.2528/PIER13110709
References

1. Nikolova, N., "Microwave imaging for breast cancer," IEEE Microwave Magazine, 78-94, Dec. 2011.
doi:10.1109/MMM.2011.942702

2. Fhager, A., S. K. Padhi, and J. Howard, "3D image reconstruction in microwave tomography using an e±cient FDTD model," IEEE Antennas Wireless Propag. Lett., Vol. 8, 1353-1356, 2009.
doi:10.1109/LAWP.2009.2039032

3. Guardiola, M., S. Capdevila, J. Romeu, and L. Jofre, "3-D microwave magnitude combined tomography for breast cancer detection using realistic breast models," IEEE Antennas Wireless Propag. Lett., Vol. 11, 1622-1625, 2012.
doi:10.1109/LAWP.2012.2235813

4. Meaney, P. M., et al. "Microwave tomography in the context of complex breast cancer imaging," Proceedings of the 32nd Annual International Conference of IEEE EMBS, 3398-3401, Aug. 2010.

5. Klemm, M., I. J. Craddock, J. A. Leendertz, A. Preece, and R. Benjamin, "Radar-based breast cancer detection using a hemispherical antenna array --- Experimental results," IEEE Trans. Ant. Propag., Vol. 57, No. 6, Jun. 2009.

6. Byrne, D., M. O'Halloran, M. Glavin, and E. Jones, "Breast cancer detection based on differential ultrawideband microwave radar," Progress In Electromagnetics Research M, Vol. 20, 231-242, 2011.
doi:10.2528/PIERM11080810

7. Lai, J. C. Y., C. B. Soh, E. Gunawan, and K. S. Low, "UWB microwave imaging for breast cancer detection --- Experimentals with heterogeneous breast phantoms," Progress In Electromagnetics Research M, Vol. 16, 19-29, 2011.

8. Flores-Tapia, D. and S. Pistorius, "Real time breast microwave radar image reconstruction using circular holography: A study of experimental feasibility," Med. Phys., Vol. 38, No. 10, 5420-5431, Oct. 2011.
doi:10.1118/1.3633922

9. Zeng, X., A. Fhager, P. Linner, M. Persson, and H. Zirath, "Zeng, X., A. Fhager, P. Linner, M. Persson, and H. Zirath, Accuracy investigation of an ultra-wideband time domain microwave imaging system," Proceedings of the 5th European Conference on Antennas and Propagation (EUCAP), 1928-1932, Apr. 2011.

10. Porter, E., E. Kirshin, A. Santorelli, M. Coates, and M. Popovic, "Time-domain multistatic radar system for microwave breast screening," IEEE Antennas Wireless Propag. Lett., Vol. 12, 229-232, 2013.
doi:10.1109/LAWP.2013.2247374

11. Byrne, D., "Ultrawideband radar for the early detection of cancer within the heterogeneous breast," Ph.D. Diss., 2012.

12. Agarwal, K., L. Pan, Y. K. Leong, M. Han, O. Y. Chan, X. Chen, and S. P. Yeo, "Practical applications of multiple signal classification," International Journal of RF and Microwave Computer-aided Engineering, Vol. 22, No. 3, 359-369, 2012.
doi:10.1002/mmce.20607

13. Arnau, O., J. Freixenet, R. Marti, and R. Zwiggelaar, "A comparison of breast tissue classification techniques," Medical Image Computing and Computer-Assisted Intervention, MICCAI, 872-879, 2006.

14. Prasad, D. P., C. Quek, and M. K. H. Leung, "A hybrid approach for breast tissue data classification," TENCON 2009-2009 IEEE Region 10 Conference, 1-4, 2009.
doi:10.1109/TENCON.2009.5396116

15. Davis, S. K., et al. "Breast tumor characterization based on ultrawideband microwave backscatter," IEEE Transactions on Biomedical Engineering, Vol. 55, No. 1, 237-246, 2008.
doi:10.1109/TBME.2007.900564

16. Kerhet, A., M. Raffetto, A. Boni, and A. Massa, "A SVM-based approach to microwave breast," cancer detection," Engineering Applications of Arti¯cial Intelligence, Vol. 19, 807-818, 2006.
doi:10.1016/j.engappai.2006.05.010

17. Conceicao, R. C., M. O'Halloran, M. Glavin, and E. Jones, "Support vector machines for the classi¯cation of early-stage breast cancer based on radar target signatures," Progress In Electromagnetics Research B, Vol. 23, 311-327, 2010.
doi:10.2528/PIERB10062407

18. Byrne, D. and Support vector machine-based ultrawide-, "Support vector machine-based ultrawide-band breast cancer detection system," Journal of Electromagnetic Waves and Applications, Vol. 25, No. 13, 1807-1816, 2011.
doi:10.1163/156939311797454015

19. Fhager, A., Y. Yu, T. McKelvey, and M. Persson, "Stroke diagnostics with a microwave helmet," Proceedings of the 7th European Conference on Antennas and Propagation (EUCAP), 845-846, Apr. 2013.

20. O'Halloran, M., F. Morgan, M. Glavin, E. Jones, R. C. Conceicao, and D. Byrne, "Bladder-state monitoring using ultra wideband radar," Proceedings of the 7th European Conference on Antennas and Propagation (EUCAP) , 624-627, Apr. 2013.

21. Conceicao, R. C., H. Medeiros, M. O'Halloran, D. Rodriguez-Herrera, D. Flores-Tapia, and S. Pistorius, "Initial classification of breast tumour phantoms using a UWB radar prototype," 2013 International Conference on Electromagnetics in Advanced Applications (ICEAA), 720-723, 2013.
doi:10.1109/ICEAA.2013.6632339

22. Kanj, H. and M. Popovic, "A novel ultra-compact broadband antenna for microwave breast tumor detection," Progress In Electromagnetics Research, Vol. 86, 169-198, 2008.
doi:10.2528/PIER08090701

23. Santorelli, A., et al. "Experimental demonstration of pulse shaping for time-domain microwave breast imaging," Progress In Electromagnetics Research, Vol. 133, 309-329, 2013.

24. Porter, E., J. Fakhoury, R. Oprisor, M. Coates, and M. Popovic, "Improved tissue phantoms for experimental validation of microwave breast cancer detection," Proceedings of the 4th European Conference on Antennas and Propagation (EUCAP), Apr. 2010.

25. Lazebnik, M., et al. "A large-scale study of the ultrawideband microwave dielectric properties of normal, benign and malignant breast tissues obtained from cancer surgeries," Phys. Med. Biol., Vol. 52, 6093-6115, 2007.
doi:10.1088/0031-9155/52/20/002

26. Lazebnik, M., E. Madsen, G. Frank, and S. Hagness, "Tissue-mimicking phantom materials for narrowband and ultrawideband microwave applications," Phys. Med. Biol., Vol. 50, 4245-4258, 2005.
doi:10.1088/0031-9155/50/18/001

27. Porter, E., E. Kirshin, A. Santorelli, and M. Popovic, "Microwave breast screening in the time-domain: Identification and compensation of measurement-induced uncertainties," Progress In Electromagnetics Research B, Vol. 55, 115-130, 2013.

28. Conceicao, R. C., et al. "Evaluation of features and classifiers for classification of early-stage breast cancer," Journal of Electromagnetic Waves and Applications, Vol. 25, No. 1, 1-14, 2011.
doi:10.1163/156939311793898350

29. Boser, B. E., I. M. Guyon, and V. N. Vapnik, "A training algorithm for optimal margin classifiers," Proceedings of the Fifth Annual Workshop on Computational Learning Theory, 144-152, 1992.
doi:10.1145/130385.130401

30. Cortes, C. and V. Vapnik, "Support-vector networks," Machine Learning, Vol. 20, No. 3, 273-297, 1995.

31. Martinez, A. and A. Kak, "PCA versus LDA," IEEE Trans. Pattern Anal. Mach. Intell, Vol. 23, No. 2, 228-233, Feb. 2001.
doi:10.1109/34.908974

32. Hsu, C.-W., C.-C. Chang, and C.-J. Lin, "A practical guide to support vector classifiocation," Tech. Rep., 2003.
doi:http://www.csie.ntu.edu.tw/cjlin/papers.html