Analysis of the Performance of the Near Field Orthogonality Sampling Method for Microwave Imaging of High Contrast Targets

Electromagnetic inverse scattering from high contrast 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 for the high contrast targets. For this purpose, the indicator of the Near Field Orthogonality Sampling Method, which is the reduced scattered field, is derived for an electrically homogeneous circular scatterer, which is centered around origin. The Near Field Orthogonality Sampling Method is classified in the qualitative microwave imaging techniques, which aim to retrieve only the shape and the position of the scatterers. Thus, the performance of the method can be assessed by comparing the energy of the indicator that falls in the exact target position with the energy that falls outside of the scatterer. Thus, 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 effect on the quality of the reconstructions of the Near Field Orthogonality Sampling Method.

PDF

___

D. Ireland, K. Bialkowski, and A. Abbosh, “Microwave imaging for brain stroke detection using born iterative method,” IET Microwaves, Antennas & Propagation, vol. 7, no. 11, pp. 909–915, 2013.

O. Güren, M. Çayören, L. T. Ergene, and I. Akduman, “Surface impedance based microwave imaging method for breast cancer screening: contrastenhanced scenario,” Physics in Medicine & Biology, vol. 59, no. 19, p. 5725, 2014.

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: A contrast source inversion approach for improved mri-based electric properties tomography,” IEEE transactions on medical imaging, vol. 34, no. 9, pp. 1788–1796, 2015.

Z. Miao and P. Kosmas, “Multiple-frequency dbimtwist algorithm for microwave breast imaging,” IEEE Transactions on Antennas and Propagation, 2017.

Ö. Özdemir and H. Haddar, “Preprocessing the reciprocity gap sampling method in buried-object imaging experiments,” IEEE Geoscience and Remote Sensing Letters, vol. 7, no. 4, pp. 756–760, 2010.

M. Bevacqua, L. Crocco, L. D. Donato, T. Isernia, and R. Palmeri, “Exploiting sparsity and field conditioning in subsurface microwave imaging of nonweak buried targets,” Radio Science, vol. 51, no. 4, pp. 301–310, 2016.

E. Bilgin and A. Yapar, “Electromagnetic scattering by radially inhomogeneous dielectric spheres,” IEEE Transactions on Antennas and Propagation, vol. 63, no. 6, pp. 2677–2685, 2015.

F. Boero, A. Fedeli, M. Lanini, M. Maffongelli, R. Monleone, M. Pastorino, A. Randazzo, A. Salvad`e, and A. Sansalone, “Microwave tomography for the inspection of wood materials: Imaging system and experimental results,” IEEE Transactions on Microwave Theory and Techniques, 2018.

M. N. Akıncı, T. Caglayan, S. Ozgur, U. Alkası, H. Ahmadzay, M. Abbak, M. C¸ ay¨oren, and ˙I. Akduman, “Qualitative microwave imaging with scattering parameters measurements,” IEEE Transactions on Microwave Theory and Techniques, vol. 63, no. 9, pp. 2730–2740, 2015.

G. Govind and M. Akhtar, “Microwave nondestructive imaging of buried objects using improved scattered-field calibration technique,” Radio Science, vol. 53, no. 1, pp. 2–14, 2018.

O. M. Bucci, N. Cardace, L. Crocco, and T. Isernia, “Degree of nonlinearity and a new solution procedure in scalar two-dimensional inverse scattering problems,” JOSA A, vol. 18, no. 8, pp. 1832–1843, 2001.

A. Kirsch, “The music-algorithm and the factorization method in inverse scattering theory for inhomogeneous media,” Inverse problems, vol. 18, no. 4, p. 1025, 2002.

R. Potthast, “A survey on sampling and probe methods for inverse problems,” Inverse Problems, vol. 22, no. 2, p. R1, 2006.

F. Cakoni, D. Colton, and P. Monk, The Linear Sampling Method in Inverse Electromagnetic Scattering. SIAM-Society for Industrial and Applied Mathematics, 2010.

W. Chew and Y. Wang, “Reconstruction of twodimensional permittivity distribution using the distorted born iterative method,” Medical Imaging, IEEE Transactions on, vol. 9, no. 2, pp. 218–225, 1990.

A. Abubakar, P. M. Van den Berg, and J. J. Mallorqui, “Imaging of biomedical data using a multiplicative regularized contrast source inversion method,” IEEE Transactions on Microwave Theory and Techniques, vol. 50, no. 7, pp. 1761–1771, 2002.

M. N. Akıncı, M. Cayoren, and I. Akduman, “Near-field orthogonality sampling method for microwave imaging: Theory and experimental verification,” IEEE Transactions on Microwave Theory and Techniques, vol. 64, no. 8, pp. 2489–2501, 2016.

M. N. Akinci, “Improving near field orthogonality sampling method for qualitative microwave imaging,” IEEE Transactions on Antennas and Propagation, 2018.

The uwcem numerical breast phantom repository, university of wisconsin. [Online]. Available: http://uwcem.ece.wisc.edul home.htm.

G. Bellizzi, O. M. Bucci, and I. Catapano, “Microwave cancer imaging exploiting magnetic nanoparticles as contrast agent,” Biomedical Engineering, IEEE Transactions on, vol. 58, no. 9, pp. 2528–2536, 2011.

M. T. Bevacqua and R. Scapaticci, “A compressive sensing approach for 3d breast cancer microwave imaging with magnetic nanoparticles as contrast agent,” IEEE transactions on medical imaging, vol. 35, no. 2, pp. 665–673, 2016.

J. D. Shea, P. Kosmas, S. C. Hagness, and B. D. Van Veen, “Contrast-enhanced microwave breast imaging,” in Antenna Technology and Applied Electromagnetics and the Canadian Radio Science Meeting, 2009. ANTEM/URSI 2009. 13th International Symposium on. IEEE, 2009, pp. 1–4.

J. D. Shea, P. Kosmas, B. D. Van Veen, and S. C. Hagness, “Contrast-enhanced microwave imaging of breast tumors: a computational study using 3D realistic numerical phantoms,” Inverse Problems, vol. 26, no. 7, p. 074009, Jul 2010.

D. Smith, O. Yurduseven, B. Livingstone, and V. Schejbal, “Microwave imaging using indirect holographic techniques,” IEEE Antennas and Propagation Magazine, vol. 56, no. 1, pp. 104–117, 2014.

E. J. Bond, X. Li, S. C. Hagness, and B. D. Van Veen, “Microwave imaging via space-time beamforming for early detection of breast cancer,” IEEE Transactions on Antennas and Propagation, vol. 51, no. 8, pp. 1690–1705, 2003.