Unsupervised time reversal based microwave imaging for breast cancer detection

Microwave breast imaging is performed by illuminating the breast tissues with a short pulse of microwaves and processing the reflections (backscatter) to create a pseudospectrum that detects the presence of the breast tumours specifying their locations. An important step in such breast cancer detection techniques is the backscatter preconditioning step for effective suppression of the clutter — signals arising from scattering mechanisms other than the tumor including the antenna reverberations and reflections from the skin-breast interface and chest wall. The paper proposes a new clutter suppression algorithm that successfully isolates the tumour response from the overall (tumour and clutter) response. The proposed DAF/EDF approach is based on a combination of the data adaptive filter (DAF) and the envelope detection filter (EDF), and does not require any prior training. The DAF/EDF algorithm is then coupled with the time reversal (TR) array imaging approaches [1, 2, 3] and tested by running finite difference, time difference (FDTD) electromagnetic simulations based on the magnetic resonance imaging (MRI) data of the human breast. Our results demonstrate the effectiveness of the DAF/EDF algorithm for microwave breast cancer detection.