This paper illustrates how breast tissue composition, modeled by different mixtures of adipose and glandular tissues, affects the accuracy of microwave breast imaging for different sizes of malignant lesions. To study this, the scattered field for different tissue composition and various tumour sizes was calculated using a Frequency Dependent Finite Difference Time Domain ((FD)2TD) approach. Images are generated from the scattered field, together with Genetic Algorithm (GA) optimization methods. The scattered field calculations show that it is strongly dependent not only on the dielectric properties and size of the breast tissue, but also on the specific tissue composition. The tumour response is the difference between scattered fields of a specific tissue composition with and without the tumour. The response of a 1.5cm tumour was found to be 6.7 times larger when it is embedded within homogeneously uniform fatty tissue than when embedded within homogeneously uniform fibro-glandular tissue. For a tumour inside a heterogeneously dense breast consisting of a mix of fi bro-glandular and fatty tissues, this value is 5.2. The consequences of the biological heterogeneity on the forward and inverse simulation, and on the accuracy of images obtained by microwave imaging using the proposed method were studied. The robustness of our approach to variations in the breast phantom was shown. This technique returned highly accurate results with millimetre resolution. The most rigorous test to date demonstrated that we are able to accurately reconstruct an image of the dielectric properties of a 7.5mm lesion embedded in fibro-glandular tissue at a depth of 6cm in a heterogeneous numerical breast phantom.

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