PIER
 
Progress In Electromagnetics Research
ISSN: 1070-4698, E-ISSN: 1559-8985
Home | Search | Notification | Authors | Submission | PIERS Home | EM Academy
Home > Vol. 105 > pp. 295-311

INVESTIGATION OF CLASSIFIERS FOR EARLY-STAGE BREAST CANCER BASED ON RADAR TARGET SIGNATURES

By R. C. Conceicao, M. O'Halloran, E. Jones, and M. Glavin

Full Article PDF (212 KB)

Abstract:
Ultra Wideband (UWB) radar has been extensively investigated as a means of detecting early-stage breast cancer. The basis for this imaging modality is the dielectric contrast between normal and cancerous breast tissue at microwave frequencies. However, based on the dielectric similarities between a malignant and a benign tumour within the breast, differentiating between these types of tissues in microwave images may be problematic. Therefore, it is important to investigate alternative methods to analyse and classify dielectric scatterers within the breast, taking into account other tumour characteristics such as shape and surface texture of tumours. Benign tumours tend to have smooth surfaces and oval shapes whereas malignant tumours tend to have rough and complex surfaces with spicules or microlobules. Consequently, one classification approach is to classify scatterers based on their Radar Target Signature (RTS), which carries important information about scatterer size and shape. In this paper, Gaussian Random Spheres (GRS) are used to model the shape and size of benign and malignant tumours. Principal Components Analysis (PCA) is used to extract information from the RTS of the tumours, while eight different combinations of tumour classifiers are analysed in terms of performance and are compared in terms of two possible approaches: Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA).

Citation:
R. C. Conceicao, 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
http://www.jpier.org/pier/pier.php?paper=10051904

References:
1. Meaney, P. M., et al., "Nonactive antenna compensation for fixed-array microwave imaging: Part II --- Imaging results," IEEE Transactions on Medical Imaging, Vol. 18, No. 6, 508-518, 1999.
doi:10.1109/42.781016

2. Meaney, P. M., et al., "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

3. Meaney, P. M., et al., "Initial clinical experience with microwave breast imaging in women with normal mammography," Academic Radiology, Vol. 14, No. 2, 207-218, 2007.
doi:10.1016/j.acra.2006.10.016

4. Bulyshev, A. E., et al., "Computational modeling of three-dimensional microwave tomography of breast cancer," IEEE Transactions on Biomedical Engineering, Vol. 48, No. 9, 1053-1056, 2001.
doi:10.1109/10.942596

5. Souvorov, A. E., et al., "Two-dimensional computer analysis of a microwave flat antenna array for breast cancer tomography," IEEE Transactions on Microwave Theory and Techniques, Vol. 48, No. 8, 1413-1415, 2000.
doi:10.1109/22.859490

6. Liu, Q. H., et al., "Active microwave imaging I --- 2-D forward and inverse scattering methods," IEEE Transactions on Microwave Theory and Techniques, Vol. 50, No. 1, 123-133, 2002.
doi:10.1109/22.981256

7. Kosmas, P. and C. M. Rappaport, "Time reversal with the FDTD method for microwave breast cancer detection," IEEE Transactions on Microwave Theory and Techniques, Vol. 53, No. 7, 2317-2323, 2005.
doi:10.1109/TMTT.2005.850444

8. Kosmas, P. and C. M. Rappaport, "FDTD-based time reversal for microwave breast cancer detection --- Localization in three dimensions," IEEE Transactions on Microwave Theory and Techniques, Vol. 54, No. 4, 1921-1927, 2006.
doi:10.1109/TMTT.2006.871994

9. Kosmas, P. and C. M. Rappaport, "A matched-filter FDTD-based time reversal approach for microwave breast cancer detection," IEEE Transactions on Antennas and Propagation, Vol. 54, No. 4, 1257-1264, 2006.
doi:10.1109/TAP.2006.872670

10. Joines, W. T., et al., "The measured electrical properties of normal and malignant human tissues from 50 to 900 MHz," Medical Physics, Vol. 21, No. 4, 1994.

11. Surowiec, A. J., et al., "Dielectric properties of breast carcinoma and the surrounding tissues," IEEE Transactions on Biomedical Engineering, Vol. 35, No. 4, 257-263, 1988.
doi:10.1109/10.1374

12. Hagness, S. C., A. Taflove, and 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

13. O'Halloran, M., M. Glavin, and E. Jones, "Channel-ranked beamformer for the early detection of breast cancer," Progress In Electromagnetics Research, Vol. 103, 153-168, 2010.
doi:10.2528/PIER10030902

14. O'Halloran, M., R. C. Conceicao, D. Byrne, M. Glavin, and E. Jones, "FDTD modeling of the breast: A review," Progress In Electromagnetics Research B, Vol. 18, 1-24, 2009.
doi:10.2528/PIERB09080505

15. Li, X. and S. C. Hagness, "A confocal microwave imaging algorithm for breast cancer detection," IEEE Microwave and Wireless Components Letters, Vol. 11, No. 3, 130-132, 2001.
doi:10.1109/7260.915627

16. Li, X., et al., "An overview of ultra-wideband microwave imaging via space-time beamforming for early-stage breast-cancer detection," IEEE Antennas and Propagation Magazine, Vol. 47, No. 1, 19-34, 2005.
doi:10.1109/MAP.2005.1436217

17. Bond, E. J., et al., "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

18. O'Halloran, M., M. Glavin, and E. Jones, "Quasi-multistatic MIST beamforming for the early detection of breast cancer," IEEE Transactions on Biomedical Engineering, Vol. 57, No. 4, 830-840, 2009.
doi:10.1109/TBME.2009.2016392

19. Lim, H. B., et al., "Confocal microwave imaging for breast cancer detection: Delay-multiply-and-sum image reconstruction algorithm," IEEE Transactions on Biomedical Engineering, Vol. 55, No. 6, 1697-1704, 2008.
doi:10.1109/TBME.2008.919716

20. O'Halloran, M., M. Glavin, and E. Jones, "Effects of fibroglan-dular tissue distribution on data-independent beamforming algo-rithms," Progress In Electromagnetics Research, Vol. 97, 141-158, 2009.
doi:10.2528/PIER09081701

21. Conceicao, R. C., M. O'Halloran, M. Glavin, and E. Jones, "Comparison of planar and circular antenna configurations for breast cancer detection using microwave imaging," Progress In Electromagnetics Research, Vol. 99, 1-19, 2009.
doi:10.2528/PIER09100204

22. Fear, E. C., et al., "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:10.1109/TBME.2002.800759

23. Conceicao, R. C., M. O'Halloran, M. Glavin, and E. Jones, "Antenna configurations for Ultra Wide Band radar detection of breast cancer," Proceedings of the SPIE, Vol. 7169, San Jose California, 2009.

24. Klemm, M., et al., "Breast cancer detection using symmetrical antenna array," Antennas and Propagation, 2007. EuCAP 2007 The Second European Conference, Edinburgh, UK, 2007.

25. Craddock, I. J., et al., "Development and application of a UWB radar system for breast imaging," 2008 Loughborough Antennas & Propagation Conference, 2008.

26. Lazebnik, M., et al., "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

27. 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," Physics in Medicine and Biology, Vol. 52, 6093-6115, 2007.
doi:10.1088/0031-9155/52/20/002

28. Chen, Y., et al., "Effect of lesion morphology on microwave signature in ultra-wideband breast imaging: A preliminary two-dimensional investigation," 2007 IEEE Antennas and Propagation Society International Symposium, 2007.

29. Chen, Y., et al., "Effect of lesion morphology on microwave signa-ture 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

30. Chen, Y., I. J. Craddock, and P. Kosmas, "Feasibility study of lesion classification via contrast-agent-aided UWB breast of lesion classification 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

31. 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

32. Muinonen, K., "Introducing the Gaussian shape hypothesis for Asteroids and Comets," Astronomy and Astrophysics, Vol. 332, 1087-1098, 1998.

33. Everitt, B. S. and G. Dunn, Applied Multivariate Data Analysis, 2nd edition, Arnold Publishers, New York, 2001.

34. Seber, G. A. F., Multivariate Observations, John Wiley & Sons, Inc, Hoboken, New Jersey, 1984.

35. Krzanowski, W. J., Principles of Multivariate Analysis: A User's Perspective, Oxford University Press, New York, 1988.

36. Raykov, T. and G. A. Marcoulides, "An introduction to applied multivariate analysis,", Routledge Taylor & Francis Group, New York, 2008.

37. Conceicao, R. C., et al., "Classification of suspicious regions within ultrawideband radar images of the breast," 16th IET Irish Signals and Systems Conference, ISSC 2008, Instn. Engg. & Tech., Galway, Ireland, UK, 2008.

38. Rangayyan, R. M., et al., "Measures of acutance and shape for classification of breast tumors," IEEE Transactions on Medical Imaging, Vol. 16, No. 6, 799-810, 1997.
doi:10.1109/42.650876

39. Guliato, et al., "Polygonal modeling of contours of breast tumors with the preservation of spicules," IEEE Transactions on Biomedical Engineering, Vol. 55, No. 1, 14-20, 2008.
doi:10.1109/TBME.2007.899310

40. Nguyen, T. M. and R. M. Rangayyan, "Shape analysis of breast masses in mammograms via the fractial dimension," Engineering in Medicine and Biology 27th Annual Conference, IEEE, Shangai, China, 2005.

41. Muinonen, K., "Chapter 11: Light scattering by stochastically shaped particles," Light Scattering by Nonspherical Particles: Theory, Measurements, and Applications, M. I. Mishchenko, J. W. Hovenier, and L. D. Travis, Editors, Academic Press, 2000.

42. Wold, H., "Estimation of principal components and related models by iterative least squares," Multivariate Analysis, K. R. Krishnaiah, Editor, 391-420, Academic Press, New York, 1996.

43. Shlens, J., "A tutorial on principal component analysis,", Mar. 25, 2003. Available: http://www.cs.princeton.edu/picasso/mats/PCA-Tutorial-Intuition jp.pdf..

44. Bartholomew, D. J., et al., "The analysis and interpretation of multivariate data for social scientists," Texts in Statistical Science, Chapman & Hall/CRC, USA, 2002.

45. Hsu, C.-W., C.-C. Chang, and C.-J. Lin, "A practical guide to support vector classification,", Apr. 3, 2010. Available: www.csie.ntu.edu.tw/┬╗cjlin/papers/guide/guide.pdf..

46. Sullivan, D. M., Electromagnetic Simulation Using the FDTD, 1st Edition, IEEE Press Series on RF and Microwave Technology, R. D. Pollard and R. Booton, Editors, Wiley-IEEE Press, New York, 2000.

47. Taflove, A. and S. C. Hagness, Computational Electrodynamics: The Finite-difference Time-domain Method, 2nd edition, Artech House, Boston, 2000.


© Copyright 2014 EMW Publishing. All Rights Reserved