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2016-03-03
3D Microwave Tomography with Huber Regularization Applied to Realistic Numerical Breast Phantoms
By
Progress In Electromagnetics Research, Vol. 155, 75-91, 2016
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
Funing Bai Ann Franchois Aleksandra 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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