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Progress In Electromagnetics Research
ISSN: 1070-4698, E-ISSN: 1559-8985
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3D MICROWAVE TOMOGRAPHY WITH HUBER REGULARIZATION APPLIED TO REALISTIC NUMERICAL BREAST PHANTOMS

By F. Bai, A. Franchois, and A. Pizurica

Full Article PDF (2,438 KB)

Abstract:
Quantitative active microwave imaging for breast cancer screening and therapy monitoring applications requires adequate reconstruction algorithms, in particular with regard to the nonlinearity and ill-posedness of the inverse problem. We employ a fully vectorial three-dimensional nonlinear inversion algorithm for reconstructing complex permittivity profiles from multi-view single-frequency scattered field data, which is based on a Gauss-Newton optimization of a regularized cost function. We tested it before with various types of regularizing functions for piecewise-constant objects from Institut Fresnel and with a quadratic smoothing function for a realistic numerical breast phantom. In the present paper we adopt a cost function that includes a Huber function in its regularization term, relying on a Markov Random Field approach. The Huber function favors spatial smoothing within homogeneous regions while preserving discontinuities between contrasted tissues. We illustrate the technique with 3D reconstructions from synthetic data at 2 GHz for realistic numerical breast phantoms from the University of Wisconsin-Madison UWCEM online repository: we compare Huber regularization with a multiplicative smoothing regularization and show reconstructions for various positions of a tumor, for multiple tumors and for different tumor sizes, from a sparse and from a denser data configuration.

Citation:
F. Bai, A. Franchois, and A. Pizurica, "3D Microwave Tomography with Huber Regularization Applied to Realistic Numerical Breast Phantoms," Progress In Electromagnetics Research, Vol. 155, 75-91, 2016.
doi:10.2528/PIER15121703
http://www.jpier.org/PIER/pier.php?paper=15121703

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