Importance of phase unwrapping for the reconstruction of microwave tomographic images

Microwave image reconstruction is typically based on a regularized least-square minimization of either the complex-valued field difference between recorded and modeled data or the logarithmic transformation of these field differences. Prior work has shown anecdotally that the latter outperforms the former in limited surveys of simulated and experimental phantom results. In this paper, we provide a theoretical explanation of these empirical findings by developing closed form solutions for the field and the inverted electromagnetic property parameters in one dimension which reveal the dependency of the estimated permittivity and conductivity on the absolute (unwrapped) phase of the measured signal at the receivers relative to the source transmission. The analysis predicts the poor performance of complex-valued field minimization as target size and/or frequency and electromagnetic contrast increase. Such poor performance is avoided by logarithmic transformation and preservation of absolute measured signal phase. Two-dimensional experiments based on both synthetic and clinical data are used to confirm these findings. Robustness of the logarithmic transformation to variation in the initial guess of the reconstructed target properties is also shown. The results are generalizable to three dimensions and indicate that the minimization form with logarithmic transformation offers image reconstruction performance characteristics that are much more desirable for medial microwave imaging applications relative to minimizing differences in complex-valued field quantities.

[1]  Howard A. Zebker,et al.  New approaches in interferometric SAR data processing , 1992, IEEE Trans. Geosci. Remote. Sens..

[2]  A. M. Nicolson,et al.  Measurement of the Intrinsic Properties of Materials by Time-Domain Techniques , 1970 .

[3]  D. Smith,et al.  Determination of effective permittivity and permeability of metamaterials from reflection and transmission coefficients , 2001, physics/0111203.

[4]  K. Paulsen,et al.  IMPORTANCE OF USING A REDUCED CONTRAST COUPLING MEDIUM IN 2D MICROWAVE BREAST IMAGING , 2003 .

[5]  C. Pichot,et al.  Microwave imaging-complex permittivity reconstruction with a Levenberg-Marquardt method , 1997 .

[6]  D. R. White,et al.  The composition of body tissues. , 1986, The British journal of radiology.

[7]  James V. Beck,et al.  Parameter Estimation in Engineering and Science , 1977 .

[8]  Robert H. Svenson,et al.  Computational modeling of three-dimensional microwave tomography of breast cancer , 2001, IEEE Transactions on Biomedical Engineering.

[9]  K. Paulsen,et al.  Microwave image reconstruction of tissue property dispersion characteristics utilizing multiple-frequency information , 2004, IEEE Transactions on Microwave Theory and Techniques.

[10]  L. Jofre,et al.  On the Possible Use of Microwave-Active Imaging for Remote Thermal Sensing , 1983 .

[11]  Matteo Pastorino,et al.  Numerical assessment concerning a focused microwave diagnostic method for medical applications , 2000 .

[12]  Paul M. Meaney,et al.  A clinical prototype for active microwave imaging of the breast , 2000 .

[13]  K. Paulsen,et al.  Near-field microwave imaging of biologically-based materials using a monopole transceiver system , 1998 .

[14]  Giovanni Leone,et al.  Inverse scattering under the distorted Born approximation for cylindrical geometries , 1999 .

[15]  L. E. Larsen,et al.  Limitations of Imaging with First-Order Diffraction Tomography , 1984 .

[16]  Ian J Craddock,et al.  Clinical experienceof breast cancer imaging using ultra-wideband microwae radar system at Bristol , 2010 .

[17]  Robert H. Svenson,et al.  Two-dimensional computer analysis of a microwave flat antenna array for breast cancer tomography , 2000 .

[18]  Jin Au Kong,et al.  Robust method to retrieve the constitutive effective parameters of metamaterials. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  B. Pogue,et al.  Microwave image reconstruction utilizing log-magnitude and unwrapped phase to improve high-contrast object recovery , 2001, IEEE Transactions on Medical Imaging.

[20]  W. Chew,et al.  Reconstruction of two-dimensional permittivity distribution using the distorted Born iterative method. , 1990, IEEE transactions on medical imaging.

[21]  J. L. van Genderen,et al.  SAR interferometry : issues, techniques, applications , 1996 .

[22]  K.A. Michalski,et al.  Electromagnetic wave theory , 1987, Proceedings of the IEEE.

[23]  P. Rocca,et al.  Evolutionary optimization as applied to inverse scattering problems , 2009 .

[24]  L. Jofre,et al.  Microwave Diffraction Tomography for Biomedical Applications , 1982 .

[25]  Weng Cho Chew,et al.  An iterative solution of the two‐dimensional electromagnetic inverse scattering problem , 1989, Int. J. Imaging Syst. Technol..

[26]  Qing Huo Liu,et al.  Performance analysis for Bayesian microwave imaging in decision aided breast tumor diagnosis , 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

[27]  Paul M. Meaney,et al.  Nonactive antenna compensation for fixed-array microwave imaging. I. Model development , 1999, IEEE Transactions on Medical Imaging.

[28]  Paul M. Meaney,et al.  Nonactive antenna compensation for fixed-array microwave imaging. II. Imaging results , 1999, IEEE Transactions on Medical Imaging.

[29]  Keith D Paulsen,et al.  Log transformation benefits parameter estimation in microwave tomographic imaging. , 2007, Medical physics.

[30]  Paul M. Meaney,et al.  The Multidimensional Phase Unwrapping Integral and Applications to Microwave Tomographical Image Reconstruction , 2006, IEEE Transactions on Image Processing.

[31]  Ian J Craddock,et al.  Breast cancer detection using symmetrical antenna array , 2007 .

[32]  K. Foster,et al.  Dielectric properties of tumor and normal tissues at radio through microwave frequencies. , 1981, The Journal of microwave power.

[33]  A. Massa,et al.  Microwave medical imaging: potentialities and limitations of a stochastic optimization technique , 2004, IEEE Transactions on Microwave Theory and Techniques.

[34]  Huabei Jiang,et al.  Model-based microwave image reconstruction: simulations and experiments. , 2004, Medical physics.

[35]  Robert H. Halstead,et al.  Matrix Computations , 2011, Encyclopedia of Parallel Computing.