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Multiple-Frequency DBIM-TwIST Algorithm for Microwave Breast Imaging

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)2507-2516
Number of pages10
Issue number5
Early online date7 Mar 2017
Publication statusPublished - May 2017


  • Multiple-frequency DBIM-TwIST_MIAO_Publishedonline7March2017_GREEN AAM

    MIAO_TAP_preprint.pdf, 3.29 MB, application/pdf


    Accepted author manuscript

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King's Authors


A novel distorted Born iterative method (DBIM)
algorithm is proposed for microwave breast imaging based on
the two-step iterative shrinkage/thresholding method. We show
that this implementation is more flexible and robust than using
traditional Krylov subspace methods such as the CGLS as
solvers of the ill-posed linear problem. This paper presents
several strategies to increase the algorithm’s robustness: a hybrid
multifrequency approach to achieve an optimal tradeoff between
imaging accuracy and reconstruction stability; a new approach to
estimate the average breast tissues properties, based on sampling
along their range of possible values and running a few DBIM
iterations to find the minimum error; and finally, a new regularization
strategy for the DBIM method based on the L1 norm
and the Pareto curve. We present reconstruction examples which
illustrate the benefits of these optimization strategies, which have
resulted in a DBIM algorithm that outperforms our previous
implementations for microwave breast imaging.

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