Search search
Publication Date
to
Vol. 17
Latest Volume
All Volumes
PIERM 139 PIERM 138 PIERM 137 PIERM 136 PIERM 135 PIERM 134 PIERM 133 PIERM 132 PIERM 131 PIERM 130 PIERM 129 PIERM 128 PIERM 127 PIERM 126 PIERM 125 PIERM 124 PIERM 123 PIERM 122 PIERM 121 PIERM 120 PIERM 119 PIERM 118 PIERM 117 PIERM 116 PIERM 115 PIERM 114 PIERM 113 PIERM 112 PIERM 111 PIERM 110 PIERM 109 PIERM 108 PIERM 107 PIERM 106 PIERM 105 PIERM 104 PIERM 103 PIERM 102 PIERM 101 PIERM 100 PIERM 99 PIERM 98 PIERM 97 PIERM 96 PIERM 95 PIERM 94 PIERM 93 PIERM 92 PIERM 91 PIERM 90 PIERM 89 PIERM 88 PIERM 87 PIERM 86 PIERM 85 PIERM 84 PIERM 83 PIERM 82 PIERM 81 PIERM 80 PIERM 79 PIERM 78 PIERM 77 PIERM 76 PIERM 75 PIERM 74 PIERM 73 PIERM 72 PIERM 71 PIERM 70 PIERM 69 PIERM 68 PIERM 67 PIERM 66 PIERM 65 PIERM 64 PIERM 63 PIERM 62 PIERM 61 PIERM 60 PIERM 59 PIERM 58 PIERM 57 PIERM 56 PIERM 55 PIERM 54 PIERM 53 PIERM 52 PIERM 51 PIERM 50 PIERM 49 PIERM 48 PIERM 47 PIERM 46 PIERM 45 PIERM 44 PIERM 43 PIERM 42 PIERM 41 PIERM 40 PIERM 39 PIERM 38 PIERM 37 PIERM 36 PIERM 35 PIERM 34 PIERM 33 PIERM 32 PIERM 31 PIERM 30 PIERM 29 PIERM 28 PIERM 27 PIERM 26 PIERM 25 PIERM 24 PIERM 23 PIERM 22 PIERM 21 PIERM 20 PIERM 19 PIERM 18 PIERM 17 PIERM 16 PIERM 14 PIERM 13 PIERM 12 PIERM 11 PIERM 10 PIERM 9 PIERM 8 PIERM 7 PIERM 6 PIERM 5 PIERM 4 PIERM 3 PIERM 2 PIERM 1
All Journals
PIER PIER B PIER C PIER M PIER Letters PIER Photonics
2011-02-17
Effects of Dielectric Heterogeneity in the Performance of Breast Tumour Classifiers
By
Raquel Cruz Conceicao,

    Dr. Raquel Cruz Conceicao

    Faculdade de Ciências - Universidade de Lisboa

    Instituto de Biofísica e Engenharia Biomédica

    Portugal

    Homepage

Martin O'Halloran,

    Dr. Martin O'Halloran

    Electronic and Electrical Engineering

    National University of Ireland Galway

    Ireland

    Homepage

Martin Glavin,

    Dr. Martin Glavin

    Electronic and Electrical Engineering

    National University of Ireland Galway

    Ireland

    Homepage

Edward Jones

    Dr. Edward Jones

    Electronic and Electrical Engineering

    National University of Ireland Galway

    Ireland

    Homepage

Progress In Electromagnetics Research M, Vol. 17, 73-86, 2011
doi:10.2528/PIERM10122402 | Google Scholar

Abstract
Breast cancer detection using Ultra Wideband Radar has been thoroughly investigated over the last decade. This breast imaging modality is based on the dielectric properties of normal and cancerous breast tissue at microwave frequencies. However, the dielectric properties of benign and malignant tumours are very similar, so tumour classification based on dielectric properties alone is not feasible. Therefore, classification methods based on the Radar Target Signature of tumours need to be further developed to classify tumours as either benign or malignant. Several studies have addressed the issue of tumour classification based on the size, shape and surface texture of the tumour. In general, these studies examined the performance of classification algorithms in primarily dielectrically homogeneous breast models. These relatively simplistic models do not provide a realistic test platform for the evaluation of tumour classification algorithms. This paper examines the classification of tumours under realistic dielectrically heterogeneous conditions. Four different heterogeneous scenarios are considered, with varying levels of heterogeneity and complexity. In this paper, the performance and robustness of tumour classification algorithms under these realistic conditions are examined and discussed.
Download Full Article (692) View Full Article volume
Citation
Raquel Cruz Conceicao, Martin O'Halloran, Martin Glavin, and Edward Jones, "Effects of Dielectric Heterogeneity in the Performance of Breast Tumour Classifiers," Progress In Electromagnetics Research M, Vol. 17, 73-86, 2011.
doi:10.2528/PIERM10122402
References

1. Hagness, S. C., A. Taflove, J. E. Bridges "Two dimensional FDTD analysis of a pulsed microwave confocal system for breast cancer detection: Fixed-focus and antenna-array sensors," IEEE Transactions on Biomedical Engineering, Vol. 45, 1470-1479, 1998.
doi:10.1109/10.730440        Google Scholar

2. Fear, E. C. and M. A. Stuchly, "Microwave system for breast tumor detection," IEEE Microwave and Guided Wave Letters, Vol. 9, No. 11, 470-472, 1999.
doi:10.1109/75.808040        Google Scholar

3. 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:10.1109/22.883861        Google Scholar

4. 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 Transactions on Antennas and Propogation, Vol. 51, No. 8, 1690-1705, 2003.
doi:10.1109/TAP.2003.815446        Google Scholar

5. Nilavalan, R., A. Gbedemah, I. J. Craddock, X. Li, and S. C. Hagness, "Numerical investigation of breast tumour detection using multi-static radar," IET Electronics Letters, Vol. 39, No. 25, 1787-1789, 2003.
doi:10.1049/el:20031183        Google Scholar

6. Bindu, G., S. J. Abraham, A. Lonappan, V. Thomas, C. K. Aanandan, and K. T. Mathew, "Active microwave imaging for breast cancer detection," Progress In Electromagnetics Research, Vol. 58, 149{-169, 2006.
doi:10.2528/PIER05081802        Google Scholar

7. Zainud-Deen, S. H., W. M. Hassen, E. El deen Ali, and K. H. Awadalla, "Breast cancer detection using a hybrid finite di®erence frequency domain and particle swarm optimization techniques," Progress In Electromagnetics Research B, Vol. 3, 35-46, 2008.
doi:10.2528/PIERB07112703        Google Scholar

8. Zhang, H., S. Y. Tan, and H. S. Tan, "A novel method for microwave breast cancer detection," Progress In Electromagnetics Research, Vol. 83, 413-434, 2008.
doi:10.2528/PIER08062701        Google Scholar

9. 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

10. AlShehri, S. A. and S. Khatun, "UWB imaging for breast cancer detection using neural network," Progress In Electromagnetics Research C, Vol. 7, 79-93, 2009.
doi:10.2528/PIERC09031202        Google Scholar

11. Byrne, D., M. O'Halloran, M. Glavin, and E. Jones, "Data independent radar beamforming algorithms for breast cancer detection," Progress In Electromagnetics Research, Vol. 107, 331-348, 2010.
doi:10.2528/PIER10061001        Google Scholar

12. Byrne, D., M. O'Halloran, E. Jones, and M. Glavin, "Transmitter-grouping robust capon beamforming for breast cancer detection," Progress In Electromagnetics Research, Vol. 108, 401-416, 2010.
doi:10.2528/PIER10090205        Google Scholar

13. Byrne , D., M. O'Halloran, M. Glavin, and E. Jones, "Contrast enhanced beamforming for breast cancer detection," Progress In Electromagnetics Research B, Vol. 28, 219-234, 2011.        Google Scholar

14. Huynh, P. T., A. M. Jarolimek, and S. Daye, "The false-negative mammogram," Radio Graphics, Vol. 18, 1137-1154, 1998.        Google Scholar

15. Elmore, J. G., M. B. Barton, V. M. Moceri, S. Polk, P. J. Arena, and S. W. Fletcher, "Ten-year risk of false positive screening mammograms and clinical breast examinations," The New England Journal of Medicine, Vol. 338, No. 16, 1089-1096, 1998.
doi:10.1056/NEJM199804163381601        Google Scholar

16. Davis, S. K., B. D. V. Veen, S. C. Hagness, and F. Kelcz, "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        Google Scholar

17. Conceicao , R. C., M. O'Halloran, E. Jones, and M. Glavin, "Investigation of classifiers for early-stage breast cancer based on radar target signatures," Progress In Electromagnetics Research, Vol. 105, 295-311, 2010.
doi:10.2528/PIER10051904        Google Scholar

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

19. McGinley, , B., M. O'Halloran, R. C. Conceicao, F. Morgan, M. Glavin, and E. Jones, "Spiking neural networks for breast cancer classification using radar target signatures," Progress In Electromagnetics Research C, Vol. 17, 79-94, 2010.
doi:10.2528/PIERC10100202        Google Scholar

20. Conceicao, R. C., M. O'Halloran, M. Glavin, and E. Jones, "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        Google Scholar

21. Conceicao, R. C., M. O'Halloran, D. Byrne, E. Jones, and M. Glavin, "Tumor classification using radar target signatures," PIERS Proceedings, 346-349, Cambridge, USA, 2010.        Google Scholar

22. Chen, Y., E. Gunawan, K. S. Low, S. Wang, C. B. Soh, and T. C. Putti, "Effect of lesion morphology on microwave signature in 2-D ultra-wideband breast imaging," IEEE Transactions on Biomedical Engineering, Vol. 55, No. 8, 2011-2021, 2008.
doi:10.1109/TBME.2008.921136        Google Scholar

23. Chen, Y., I. J. Craddock, P. Kosmas, M. Ghavami, and P. Rapajic, "Application of the MIMO radar technique for lesion classi¯cation in UWB breast cancer detection," 17th European Signal Processing Conference (EUSIPCO), 759-763, Glasgow, Scotland, 2009.        Google Scholar

24. Chen, Y., I. J. Craddock, P. Kosmas, M. Ghavami, and P. Rapajic, "Multiple-input multiple-output radar for lesion classification in ultrawideband breast imaging," IEEE Journal of Selected Topics in Signal Processing, Vol. 4, No. 1, 187-201, 2010.
doi:10.1109/JSTSP.2009.2038975        Google Scholar

25. Chen, Y., I. J. Craddock, and P. Kosmas, "Feasibility study of lesion classi¯cation via contrast-agent-aided UWB breast imaging," IEEE Transactions on Biomedical Engineering, Vol. 57, No. 5, 1003-1007, 2010.
doi:10.1109/TBME.2009.2038788        Google Scholar

26. Teo, J., Y. Chen, C. B. Soh, E. Gunawan, K. S. Low, T. C. Putti, and S. Wang, "Breast lesion classification using ultrawideband early time breast lesion response," IEEE Transactions on Antennas and Propagation, Vol. 58, No. 8, 2604-2613, 2010.
doi:10.1109/TAP.2010.2050423        Google Scholar

27., University of Wisconsin --- Computational Electromagnetics Laboratory (UWCEM). Last Accessed: 22/09/2010. Availablefrom: http://uwcem.ece.wisc.edu/.        Google Scholar

28. Lazebnik, M., L. McCartney, D. Popovic, C. B. Watkins, M. J. Lindstrom, J. Harter, S. Sewall, A. Magliocco, J. H. Booske, M. Okoniewski, and , "A large-scale study of the ultrawideband microwave dielectric properties of normal breast tissue obtained from reduction surgeries," Physics in Medicine and Biology, Vol. 52, 2637-2656, 2007.
doi:10.1088/0031-9155/52/10/001        Google Scholar

29. Lazebnik, , M., D. Popovic, L. McCartney, C. B. Watkins, M. J. Lindstrom, J. Harter, S. Sewall, T. Ogilvie, A. Magliocco, and T. M. Breslin, "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, 6093-6115, 2007.
doi:10.1088/0031-9155/52/20/002        Google Scholar

30. Muinonen, K., "Introducing the gaussian shape hypothesis for asteroids and comets," Astronomy and Astrophysics,, Vol. 332, 1087-1098, 1998.        Google Scholar

31. Muinonen, K., Light Scattering by Stochastically Shaped Particles,in Light Scattering by Nonspherical Particles: Theory, Measurements, and Applications, M. I. Mishchenko, J. W. Hovenier and L. D. Travis (eds.), Chapter 11, Academic Press, 2000.

Download Full Article (692) View Full Article volume


The EM Academy piers.org jpier.org Who's Who in EM
Copyright © 2022 The Electromagnetics Academy. All Rights Reserved.