The effects of the fibroglandular tissue distribution of the breast on data-independent microwave imaging algorithms are investigated in this paper. A data-independent beamformer is a beamformer whose weights do not depend on the array data and are chosen, based on a channel model, to compensate for path-dependent attenuation and phase effects. The effectiveness and robustness of data-independent UWB beamforming algorithms relies upon two specific characteristics of breast tissue at microwave frequencies: firstly, that there exists a significant dielectric contrast between cancerous tissue and normal healthy breast tissue; secondly, that the propagation, attenuation and phase characteristics of normal tissue allow for constructive addition of the UWB returns using the Confocal Microwave Imaging (CMI) technique. However, two recent studies by Lazebnik et al. have highlighted a significant dielectric contrast between normal adipose and fibroglandular tissue within the breast. These results suggest a much more difficult imaging scenario where clutter due to fibroglandular tissue is a significant concern and that constructive addition of backscattered signals is potentially much more problematic than previously assumed. In this paper, three existing data-independent beamformers are tested on several different breast models, examining the effect of different fibroglandular tissue distribution on the performance of the data-independent imaging algorithms.
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