http://iet.metastore.ingenta.com
1887

Compressive sensing for microwave breast cancer imaging

Compressive sensing for microwave breast cancer imaging

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Signal Processing — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The long time for collecting the data and a considerable amount of data are important technical challenges in microwave imaging for the detection of breast cancer. From the other point of view, compressive sensing (CS) is an interesting representation and analysis of sparse signals. In this study, a new imaging method for monostatic ultra-wideband microwave imaging of breast cancer using CS is presented. Instead of using all of the conventional radar returned signals, a few received signals, by random choosing the antenna, are sufficient for obtaining reliable images even at high noise levels. Using simulations done, it is shown that sparser images are obtained comparing to the delay-and-sum beamforming technique using only a few received signals.

References

    1. 1)
      • 1. Fear, E.C., Li, X., Hagness, S.C., et al: ‘Confocal microwave imaging for breast cancer detection: localization of tumors in three dimensions’, IEEE Trans. Biomed. Eng., 2002, 49, (8), pp. 812822.
    2. 2)
      • 2. Fear, E.C., Stuchly, M.A.: ‘Microwave detection of breast cancer’, IEEE Trans. Microw. Theory Tech., 2000, 48, (11), pp. 18541863.
    3. 3)
      • 3. Lim, H.B., Nhung, N.T.T., Li, E.-P., et al: ‘Confocal microwave imaging for breast cancer detection delay-multiply-and-sum image reconstruction algorithm’, IEEE Trans. Biomed. Eng., 2008, 55, (6), pp. 16971704.
    4. 4)
      • 4. Arabshahi, F., Monajemi, S., Sheikhzadeh, H., et al: ‘A frequency domain MVDR beamformer for UWB microwave breast cancer imaging in dispersive mediums’. IEEE Int. Symp. on Signal Processing and Information Technology (ISSPIT), December 2013.
    5. 5)
      • 5. Zhu, X., Zhao, J.W., Song, J., et al: ‘Microwave-induced thermal acoustic tomography for breast tumor based on compressive sensing’, IEEE Trans. Biomed. Eng., 2013, 60, (5), pp. 12981307.
    6. 6)
      • 6. Chen, S., Donoho, D.L., Saunders, M.A.: ‘Atomic decomposition by basis pursuit’, SIAM J. Sci. Comput., 1998, 20, (1), pp. 3361.
    7. 7)
      • 7. Candès, E.J., Tao, T.: ‘The Dantzig selector: statistical estimation when p is much larger than n’, Ann. Statist., 2007, 35, pp. 23132351.
    8. 8)
      • 8. Tibshirani, R.: ‘Regression shrinkage and selection via lasso’, J. R. Statist. Soc. Ser. B, 1996, 58, pp. 267288.
    9. 9)
      • 9. Gurbuz, A.C., McClellan, J.H., Scott, W.R.: ‘Compressive sensing data acquisition and imaging method for stepped frequency GPRs’, IEEE Trans. Signal Process., 2009, 57, (7), pp. 26402650.
    10. 10)
      • 10. Gurbuz, A.C., McClellan, J.H., Scott, W.R.: ‘Compressive sensing for subsurface imaging using ground penetrating radar’, Signal Process., 2009, 89, pp. 19591972.
    11. 11)
      • 11. Qiong, H., Lele Qu, Q., Bingheng, W., et al: ‘UWB through-wall imaging based on compressive sensing’, IEEE Trans. Geosci. Remote Sens., 2010, 48, (3), pp. 14081415.
    12. 12)
      • 12. Gurbuz, A.C., McClellan, J.H., Scott, W.R.: ‘Compressive sensing of underground structures using GPR’, Digit. Signal Process., 2012, 22, (1), pp. 6673.
    13. 13)
      • 13. Xie, Y., Guo, B., Xu, L., et al: ‘Multistatic adaptive microwave imaging for early breast cancer detection’, IEEE Trans. Biomed. Eng., 2006, 55, (8), pp. 16471657.
    14. 14)
      • 14. Elahi, M.A., Shahzad, A., Glavin, M., et al: ‘Hybrid artifact removal for confocal microwave breast imaging’, IEEE Antennas Wirel. Propag. Lett., 2014, 13, pp. 149152.
    15. 15)
      • 15. Bond, E.J., Li, X., Hagness, S.C., et al: ‘Microwave imaging via space-time beamforming for early detection of breast cancer’, IEEE Trans. Antennas Propag., 2003, 51, (8), pp. 16901705.
    16. 16)
      • 16. Maklad, B., Curtis, C., Fear, E., et al: ‘Neighborhood-based algorithm to facilitate the reduction of skin reflections in radar-based microwave imaging’, Prog. Electromagn. Res. B, 2012, 39, pp. 115139.
    17. 17)
      • 17. Nilavalan, R., Gbedemah, A., Craddock, I.J., et al: ‘Numerical investigation of breast tumour detection using multi-static radar’, Electron. Lett., 2003, 39, (25), pp. 17871789.
    18. 18)
      • 18. Fear, E.C., Bourqui, J., Curtis, C., et al: ‘Microwave breast imaging with a monostatic radar-based system: a study of application to patients’, IEEE Trans. Microw. Theory Tech., 2013, 61, (5), pp. 21192128.
    19. 19)
      • 19. University of Wisconsin Computational Electromagnetics Laboratory UWCEM Numerical Breast Phantom Repository. Available at http://uwcem.ece.wisc.edu.
    20. 20)
      • 20. Zastrow, E., Davis, S., Lazebnik, M., et al: ‘Development of anatomically realistic numerical breast phantoms with accurate dielectric properties for modeling microwave interactions with the human breast’, IEEE Trans. Biomed. Eng., 2008, 55, (12), pp. 27922800.
    21. 21)
      • 21. Lazebnik, M., Popovic, D., McCartney, L., 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., 2007, 52, pp. 60936115.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-spr.2015.0537
Loading

Related content

content/journals/10.1049/iet-spr.2015.0537
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address