volume | PIER Journals

Abstract

One of the most promising alternative imaging modalities for breast cancer detection involved the use of microwave radar systems. A critical component of any radar-based imaging system for breast cancer detection is the early-stage artifact removal algorithm. Many existing artifact removal algorithms are based on simplifying assumptions about the degree of commonality in the artifact across all channels. However, several real-world clinical scenarios could result in greater variation in the early-stage artifact, making the artifact removal process much more difficult. In this study, a range of existing artifact removal algorithms, coupled with algorithms adapted from Ground Penetrating Radar applications, are compared across a range of appropriate performance metrics.

1. Hagness, S. C., A. Taflove, and J. E. Bridges, "Three-dimensional FDTD analysis of a pulsed microwave confocal system for breast cancer detection: Design of an antenna-array element," IEEE Trans. on Antennas and Propagat., Vol. 47, No. 5, 783-791, May 1999.
doi:10.1109/8.774131 Google Scholar

2. 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 Trans. on Biomed. Eng., Vol. 49, No. 8, 812-822, August 2002.
doi:10.1109/TBME.2002.800759 Google Scholar

3. Bond, E. J., X. Li, S. C. Hagness, and B. D. V. Veen, "Microwave imaging via space-time beamforming for early detection of breast cancer," IEEE Trans. on Antennas and Propagat., Vol. 8, 1690-1705, August 2003.
doi:10.1109/TAP.2003.815446 Google Scholar

4. Li, X., E. J. Bond, S. C. Hagness, B. D. V. Veen, and D. van der Weide, "Three-dimensional microwave imaging via space-time beamforming for breast cancer detection," IEEE AP-S International Symposium and USNC/USRI Radio Science Meeting, San Antonio, TX, USA, June 2002. Google Scholar

5. Xie, Y., B. Guo, J. Li, and P. Stoica, "Novel multistatic adaptive microwave imaging methods for early breast cancer detection," EURASIP J. Appl. Si. P., Vol. 2006, Article ID: 91961, 1-13, 2006. Google Scholar

6. Moriyama, T., Z. Meng, and T. Takenaka, "Forward-backward time-stepping method combined with genetic algorithm applied to breast cancer detection," Microwave and Optical Technology Letters, Vol. 53, No. 2, 438-442, 2011.
doi:10.1002/mop.25699 Google Scholar

7. 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 M, Vol. 18, 179-195, 2011. Google Scholar

8. Klemm, M., I. J. Craddock, J. A. Leendertz, A. Preece, and R. Benjamin, "Improved delay-and-sum beamforming algorithm for breast cancer detection," International Journal of Antennas and Propagation, Vol. 2008, Article ID: 761402, 9 Pages, 2008. Google Scholar

9. Sill, J. and E. Fear, "Tissue sensing adaptive radar for breast cancer detection-experimental investigation of simple tumor models," IEEE Transactions on Microwave Theory and Techniques, Vol. 53, No. 11, 3312-3319, 2005.
doi:10.1109/TMTT.2005.857330 Google Scholar

10. Woody, C. D., "Characterization of an adaptive filter for the analysis of variable latency neuroelectric signals," Medical and Biological Engineering, Vol. 5, No. 6, 539-554, 1967.
doi:10.1007/BF02474247 Google Scholar

11. Abujarad, F., A. Jostingmeier, and A. Omar, "Clutter removal for landmine using different signal processing techniques," Proceedings of the Tenth International Conference on Ground Penetrating Radar, GPR, 697-700, 2004. Google Scholar

12. Verma, P., A. Gaikwad, D. Singh, and M. Nigam, "Analysis of clutter reduction techniques for through wall imaging in UWB range," Progress In Electromagnetics Research B, Vol. 17, 29-48, 2009.
doi:10.2528/PIERB09060903 Google Scholar

13. Zhi, W. and F. Chin, "Entropy-based time window for artifact removal in uwb imaging of breast cancer detection," IEEE Signal Processing Letters, Vol. 13, No. 10, 585-588, 2006.
doi:10.1109/LSP.2006.876346 Google Scholar

14. Maskooki, A., E. Gunawan, C. B. Soh, and K. S. Low, "Frequency domain skin artifact removal method for ultra-wideband breast cancer detection," Progress In Electromagnetics Research, Vol. 98, 299-314, 2009.
doi:10.2528/PIER09101302 Google Scholar

15. Piou, J., "A state identification method for 1-D measurements with gaps," Proc. American Institute of Aeronautics and Astronautics Guidance Navigation and Control Conf., 2005. Google Scholar

16. Wax, M. and T. Kailath, "Detection of signals by information theoretic criteria," IEEE Transactions on Acoustics, Speech and Signal Processing, Vol. 33, No. 2, 387-392, 1985.
doi:10.1109/TASSP.1985.1164557 Google Scholar

17. Zastrow, E., S. K. Davis, M. Lazebnik, F. Kelcz, B. D. V. Veen, and S. C. Hagness, "Database of 3D grid-based numerical breast phantoms for use in computational electromagnetics simulations," , Department of Electrical and Computer Engineering University of -Wisconsin-Madison, 2008, [online], available: httphttp://uwcem.ece.wisc.edu/home.htm. Google Scholar

18. Kumar, R. and M. Rattan, "Analysis of various quality metrics for medical image processing," International Journal, Vol. 2, No. 11, 2012. Google Scholar

Mr. Muhammad Adnan Elahi

Dr. Martin Glavin

Dr. Edward Jones

Dr. Martin O'Halloran