This paper presents a novel stochastic microwave method for the detection, location and reconstruction of electric properties of breast cancer in a simplified breast phantom. The method is based on the inversion of time domain data. The problem is recast as an optimization one by defining a suitable cost function which is then minimized using an efficient evolutionary algorithm. Selected numerical simulations of a simplified three dimensional breast model and a realistic numerical phantom based on magnetic resonance images (MRIs) are carried out to assess the capabilities of the method. The results obtained show that the proposed method is able to reconstruct the properties of a tumor-like inclusion to a reasonable degree of accuracy.
Conventional radar-based image reconstruction techniques fail when they are applied to
heterogeneous breast tissue, since the underlying in-breast relative permittivity is unknown or assumed
to be constant. This results in a systematic error during the process of image formation. A recent
trend in microwave biomedical imaging is to extract the relative permittivity from the object under
test to improve the image reconstruction quality and thereby to enhance the diagnostic assessment.
In this paper, we present a novel radar-based methodology for microwave breast cancer detection in
heterogeneous breast tissue integrating a 3D map of relative permittivity as a priori information. This
leads to a novel image reconstruction formulation where the delay-and-sum focusing takes place in
time rather than range domain. Results are shown for a heterogeneous dense (class-4) and a scattered
fibroglandular (class-2) numerical breast phantom using Bristol's 31-element array configuration.
Estimation of the skin location is important for radarbased detection of breast cancer. This paper presents a 3D algorithm for mapping the breast surface. The algorithm's performance is assessed based on numerical data extracted from FDTD simulations.
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