volume | PIER Journals

2020-09-24

Detection of Depth of the Tumor in Microwave Imaging Using Ground Penetrating Radar Algorithm

Vanaja Bensingh,

Dr. Vanaja Bensingh

Department of Electronics of Computer Science and Engineering (AIML)

Easwari Engineering College

India

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John Bosco Joselin Jeya Sheela,

Dr. John Bosco Joselin Jeya Sheela

Rajalakshmi Institute of Technology

India

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Rahul Krishnan,

Dr. Rahul Krishnan

Department of Electronics and Communication Engineering

Adi Shankara Institute of Engineering and Technology

India

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Kandasamy Lalitha,

Dr. Kandasamy Lalitha

SRM Institute of Science and Technology

India

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Sasirekha Devarajulu

Dr. Sasirekha Devarajulu

Rajalakshmi Engineering College

India

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Progress In Electromagnetics Research M, Vol. 96, 191-202, 2020

doi:10.2528/PIERM20062201 | Google Scholar

Abstract

Microwave Imaging (MI) is a new technique for detecting breast cancer using electrical property difference between the non-malignant and malignant tissues present in the breast. Numerous studies show that detecting the depth of the tumor is the essential measure in determining additional management. Developing evidence in many of the literature surveys illustrate that detecting tumor depth is a precise parameter for identifying the affected area. Thus, Ground Penetrating Radar (GPR) algorithm is applied successfully to detect the exact depth of the malignant tissue. Generally, GPR is originally conceived for archaeological investigations, building condition assessment, detection of buried mines, etc. But here an effort has been made to apply GPR to Radar-based breast cancer detection. The simulated bandwidth of the proposed UWB antenna starts at 2.4GHz and ends at 4.7 GHz. The electromagnetic wave reflected due to dielectric property variation is used by GPR algorithm to identify the depth of the tumor. Before applying a depth migration technique, preprocessing steps like Cartesian form transformation, Hermitian Signal Processing, and Inverse Fast Fourier Transform (IFFT) have to be followed in the backscattered signal to convert positive frequency data into time-domain data. Depth details can be noticed in the migrated image, after applying the migration procedure. Results show that GPR algorithm can be effectively used for detecting the tumor embedded in the depth of the breast tissue. To understand the effectiveness of this imaging scheme, an experimental analysis is done using a combination of wheat flour and water-petroleum jelly. The measured impedance bandwidth of the UWB antenna ranges from 2.8 GHz to 4.48 GHz. The observation is done for a known spherical tumor of diameter 13mm which is placed at different depths from the skin layer. While applying the algorithm in the received backscattered signal, we were able to detect correctly the tumor at a depth of 45mm embedded in the breast tissue. The experimental results are compared with simulation ones to validate the aptness of a microwave imaging approach for detecting the depth of the tumor.

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Vanaja Bensingh, John Bosco Joselin Jeya Sheela, Rahul Krishnan, Kandasamy Lalitha, and Sasirekha Devarajulu, "Detection of Depth of the Tumor in Microwave Imaging Using Ground Penetrating Radar Algorithm," Progress In Electromagnetics Research M, Vol. 96, 191-202, 2020.
doi:10.2528/PIERM20062201

References

1. Mendat, C. C., D. Mislan, and L. Hession-Kunz, "Patient comfort from the technologist perspective: Factors to consider in mammographic imaging," International Journal of Women's Health, Vol. 9, 359, 2017.
doi:10.2147/IJWH.S129817 Google Scholar

2. Chan, H. H., G. Lo, and P. S. Cheung, "Is pain from mammography reduced by the use of a radiolucent MammoPad? Local experience in Hong Kong," Hong Kong Med. J., Vol. 22, No. 3, 210-215, 2016.
doi:10.12809/hkjr1916939 Google Scholar

3. Kosus, N., A. Kosus, M. Duran, S. Simavlı, and N. Turhan, "Comparison of standard mammography with digital mammography and digital infrared thermal imaging for breast cancer screening," Journal of the Turkish German Gynecological Association, Vol. 11, No. 3, 152, 2010.
doi:10.5152/jtgga.2010.24 Google Scholar

4. Heywang-Kobrunner, S. H., A. Hacker, and S. Sedlacek, "Advantages and disadvantages of mammography screening," Breast Care, Vol. 6, No. 3, 199-207, 2011.
doi:10.1159/000329005 Google Scholar

5. Fernandez, M. G., Y. A. Lopez, A. A. Arboleya, B. G. Valdes, Y. R. Vaqueiro, F. L. H. Andres, and A. P. Garcıa, "Synthetic aperture radar imaging system for landmine detection using a ground penetrating radar on board a unmanned aerial vehicle," IEEE Access, Vol. 6, 45100-45112, 2018.
doi:10.1109/ACCESS.2018.2863572 Google Scholar

6. Selvaraj, V. and P. Srinivasan, "Interaction of an EM wave with the breast tissue in a microwave imaging technique using an ultra-wideband antenna," Biomedical Research, Vol. 28, No. 3, 1025-1030, 2017. Google Scholar

7. Kuwahara, Y. and A. M. Malik, "Microwave imaging for early breast cancer detection," New Perspect. Breast Imaging, 45-71, IntechOpen, 2017. Google Scholar

8. Zhang, H., S. Y. Tan, and H. S. Tan, "A novel method for microwave breast cancer detection," 2008 Asia-Pacific Microwave Conference, 1-4, IEEE, 2008. Google Scholar

9. Chen, Y., E. Gunawan, Y. Kim, K. Low, and C. Soh, "UWB microwave imaging for breast cancer detection: Tumor/clutter identification using a time of arrival data fusion method," 2006 IEEE Antennas and Propagation Society International Symposium, 255-258, IEEE, 2006.
doi:10.1109/APS.2006.1710504 Google Scholar

10. Chen, Y., E. Gunawan, K. S. Low, S. C. Wang, C. B. Soh, and L. L. Thi, "Time of arrival data fusion method for two-dimensional ultrawideband breast cancer detection," IEEE Transactions on Antennas and Propagation, Vol. 55, No. 10, 2852-2865, 2007.
doi:10.1109/TAP.2007.905868 Google Scholar

11. Unal, I, B. Turetken, and Y. Cotur, "Microwave imaging of breast cancer tumor inside voxel-based breast phantom using conformal antennas," 2014 XXXIth URSI General Assembly and Scientific Symposium (URSI GASS), 1-4, IEEE, 2014. Google Scholar

12. Computer Simulation Technology (CST) microwave studio software, , , version 2010.

13. Tiang, S. S., M. S. Hathal, T. F. Zanoon, M. F. Ain, and M. Z. Abdullah, "Radar sensing featuring biconical antenna and enhanced delay and sum algorithm for early stage breast cancer detection," Progress In Electromagnetics Research B, Vol. 46, 299-316, 2013.
doi:10.2528/PIERB12102201 Google Scholar

14. Borja, B., J. A. Tirado-Mendez, and H. Jardon-Aguilar, "An overview of UWB antennas for microwave imaging systems for cancer detection purposes," Progress In Electromagnetics Research B, Vol. 80, 173-198, 2018.
doi:10.2528/PIERB18030302 Google Scholar

15. Amdaouch, I., O. Aghzout, A. Naghar, A. V. Alejos, and F. J. Falcone, "Breast tumor detection system based on a compact UWB antenna design," Progress In Electromagnetics Research M, Vol. 64, 123-133, 2018.
doi:10.2528/PIERM17102404 Google Scholar

16. Adnan, S., R. Abd-Alhameed, C. H. See, H. I. Hraga, I. T. Elfergani, and D. Zhou, "A compact UWB antenna design for breast cancer detection," PIERS Online, Vol. 6, No. 2, 129-132, 2010.
doi:10.2529/PIERS091029055334 Google Scholar

17. AlShehri, S. A., S. Khatun, A. B. Jantan, R. S. A. Raja Abdullah, R. Mahmud, and Z. Awang, "Experimental breast tumor detection using NN-based UWB imaging," Progress In Electromagnetics Research, Vol. 111, 447-465, 2011.
doi:10.2528/PIER10110102 Google Scholar