Analysis of The Performance of The NOSM For High Contrast Targets

Year 2019, , 224 - 232, 01.04.2019

Mehmet Nuri Akıncı

https://doi.org/10.16984/saufenbilder.471026

Abstract

Electromagnetic inverse scattering from high con-
trast scatterers is of special importance, especially in Microwave
Imaging, wherein the recent technology aims to image high
contrast scatterer. To this purpose, this paper presents an analysis
of the performance of the recently proposed microwave imaging
technique of the Near Field Orthogonality Sampling (NOSM)
for the high contrast targets. For this purpose, the indicator of
the NOSM, which is the reduced scattered field, is derived for
an electrically homogeneous circular scatterer, which is centered
around origin. Next, the ratios of the indicator energy densities
inside and outside of the target is defined as a quality metric.
After, the quality metric and its expressions for limiting cases
(i.e. where the electrical parameter of the the target is too
large or too low) are derived in terms of the background’s
and target’s electrical properties. Then, the introduced metric
is computed and plotted for a popular application, which is
microwave imaging of the breast. Obtained results show that
the high contrasts between the target and the background does
not have an important affect on the quality of the reconstructions
of the NOSM.

Keywords

Near Field Orthogonality Sampling Method, Microwave Imaging

References

• [1] D. Ireland, K. Bialkowski, and A. Abbosh, “Microwave imaging forbrain stroke detection using born iterative method,” IET Microwaves,Antennas & Propagation, vol. 7, no. 11, pp. 909–915, 2013.
• [2] O. Güren, M. Cayoren, L. T. Ergene, and I. Akduman, “Surfaceimpedance based microwave imaging method for breast cancer screen-ing: contrast-enhanced scenario,” Physics in Medicine & Biology,vol. 59, no. 19, p. 5725, 2014.
• [3] E. Balidemaj, C. A. van den Berg, J. Trinks, A. L. van Lier, A. J.Nederveen, L. J. Stalpers, H. Crezee, and R. F. Remis, “Csi-ept: Acontrast source inversion approach for improved mri-based electricproperties tomography,” IEEE transactions on medical imaging, vol. 34,no. 9, pp. 1788–1796, 2015.
• [4] Z. Miao and P. Kosmas, “Multiple-frequency dbim-twist algorithmfor microwave breast imaging,” IEEE Transactions on Antennas andPropagation, 2017.
• [5] O. Ozdemir and H. Haddar, “Preprocessing the reciprocity gap samplingmethod in buried-object imaging experiments,” IEEE Geoscience andRemote Sensing Letters, vol. 7, no. 4, pp. 756–760, 2010.
• [6] M. Bevacqua, L. Crocco, L. D. Donato, T. Isernia, and R. Palmeri,“Exploiting sparsity and field conditioning in subsurface microwaveimaging of nonweak buried targets,” Radio Science, vol. 51, no. 4, pp.301–310, 2016.
• [7] E. Bilgin and A. Yapar, “Electromagnetic scattering by radially in-homogeneous dielectric spheres,” IEEE Transactions on Antennas andPropagation, vol. 63, no. 6, pp. 2677–2685, 2015.
• [8] F. Boero, A. Fedeli, M. Lanini, M. Maffongelli, R. Monleone, M. Pas-torino, A. Randazzo, A. Salvade, and A. Sansalone, “Microwave to-mography for the inspection of wood materials: Imaging system andexperimental results,” IEEE Transactions on Microwave Theory andTechniques, 2018.
• [9] M. N. Akıncı, T. C¸ a˘glayan, S. Ozgur, U. Alkas¸ı, H. Ahmadzay, M. Ab-bak, M. Cayoren, and ˙I. Akduman, “Qualitative microwave imaging withscattering parameters measurements,” IEEE Transactions on MicrowaveTheory and Techniques, vol. 63, no. 9, pp. 2730–2740, 2015.
• [10] G. Govind and M. Akhtar, “Microwave nondestructive imaging of buriedobjects using improved scattered-field calibration technique,” RadioScience, vol. 53, no. 1, pp. 2–14, 2018.
• [11] O. M. Bucci, N. Cardace, L. Crocco, and T. Isernia, “Degree ofnonlinearity and a new solution procedure in scalar two-dimensionalinverse scattering problems,” JOSA A, vol. 18, no. 8, pp. 1832–1843,2001.
• [12] A. Kirsch, “The music-algorithm and the factorization method in inversescattering theory for inhomogeneous media,” Inverse problems, vol. 18,no. 4, p. 1025, 2002.
• [13] R. Potthast, “A survey on sampling and probe methods for inverseproblems,” Inverse Problems, vol. 22, no. 2, p. R1, 2006.
• [14] F. Cakoni, D. Colton, and P. Monk, The Linear Sampling Method inInverse Electromagnetic Scattering. SIAM-Society for Industrial andApplied Mathematics, 2010.
• [15] W. Chew and Y. Wang, “Reconstruction of two-dimensional permittivitydistribution using the distorted born iterative method,” Medical Imaging,IEEE Transactions on, vol. 9, no. 2, pp. 218–225, 1990.
• [16] A. Abubakar, P. M. Van den Berg, and J. J. Mallorqui, “Imaging ofbiomedical data using a multiplicative regularized contrast source inver-sion method,” IEEE Transactions on Microwave Theory and Techniques,vol. 50, no. 7, pp. 1761–1771, 2002.
• [17] M. N. Akıncı, M. Cayoren, and I. Akduman, “Near-field orthogonalitysampling method for microwave imaging: Theory and experimentalverification,” IEEE Transactions on Microwave Theory and Techniques,vol. 64, no. 8, pp. 2489–2501, 2016.
• [18] M. N. Akinci, “Improving near field orthogonality sampling method forqualitative microwave imaging,” IEEE Transactions on Antennas andPropagation, 2018.
• [19] The uwcem numerical breast phantom repository, university ofwisconsin. [Online]. Available: http://uwcem.ece.wisc.edul home.htm.
• [20] G. Bellizzi, O. M. Bucci, and I. Catapano, “Microwave cancer imagingexploiting magnetic nanoparticles as contrast agent,” Biomedical Engi-neering, IEEE Transactions on, vol. 58, no. 9, pp. 2528–2536, 2011.
• [21] M. T. Bevacqua and R. Scapaticci, “A compressive sensing approachfor 3d breast cancer microwave imaging with magnetic nanoparticles ascontrast agent,” IEEE transactions on medical imaging, vol. 35, no. 2,pp. 665–673, 2016.[22] J. D. Shea, P. Kosmas, S. C. Hagness, and B. D. Van Veen, “Contrast-enhanced microwave breast imaging,” in Antenna Technology and Ap-plied Electromagnetics and the Canadian Radio Science Meeting, 2009.ANTEM/URSI 2009. 13th International Symposium on. IEEE, 2009,pp. 1–4.
• [23] J. D. Shea, P. Kosmas, B. D. Van Veen, and S. C. Hagness, “Contrast-enhanced microwave imaging of breast tumors: a computational studyusing 3D realistic numerical phantoms,” Inverse Problems, vol. 26, no. 7,p. 074009, Jul 2010.
• [24] D. Smith, O. Yurduseven, B. Livingstone, and V. Schejbal, “Microwaveimaging using indirect holographic techniques,” IEEE Antennas andPropagation Magazine, vol. 56, no. 1, pp. 104–117, 2014.
• [25] E. J. Bond, X. Li, S. C. Hagness, and B. D. Van Veen, “Microwaveimaging via space-time beamforming for early detection of breastcancer,” IEEE Transactions on Antennas and Propagation, vol. 51, no. 8,pp. 1690–1705, 2003.