Vol. 17

Front:[PDF file] Back:[PDF file]
Latest Volume
All Volumes
All Issues
2011-02-17

Effects of Dielectric Heterogeneity in the Performance of Breast Tumour Classifiers

By Raquel Cruz Conceicao, Martin O'Halloran, Martin Glavin, and Edward Jones
Progress In Electromagnetics Research M, Vol. 17, 73-86, 2011
doi:10.2528/PIERM10122402

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.

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
http://www.jpier.org/PIERM/pier.php?paper=10122402

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

    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

    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

    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

    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

    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

    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

    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

    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

    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

    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

    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

    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.

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

    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

    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

    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

    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

    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

    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

    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.

    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

    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.

    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

    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

    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

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

    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

    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

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

    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.