Novel multistatic adaptive microwave imaging methods for early breast cancer detection

Authors:
Yao Xie;Bin Guo;Jian Li;Petre Stoica
Affiliations:
Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL;Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL;Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL;Systems and Control Division, Department of Information Technology, Uppsala University, Uppsala, Sweden
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2006

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Abstract

Multistatic adaptive microwave imaging (MAMI) methods are presented and compared for early breast cancer detection. Due to the significant contrast between the dielectric properties of normal and malignant breast tissues, developing microwave imaging techniques for early breast cancer detection has attracted much interest lately. MAMI is one of the microwave imaging modalities and employs multiple antennas that take turns to transmit ultra-wideband (UWB) pulses while all antennas are used to receive the reflected signals. MAMI can be considered as a special case of the multi-input multi-output (MIMO) radar with the multiple transmitted waveforms being either UWB pulses or zeros. Since the UWB pulses transmitted by different antennas are displaced in time, the multiple transmitted waveforms are orthogonal to each other. The challenge to microwave imaging is to improve resolution and suppress strong interferences caused by the breast skin, nipple, and so forth. The MAMI methods we investigate herein utilize the data-adaptive robust Capon beamformer (RCB) to achieve high resolution and interference suppression. We will demonstrate the effectiveness of our proposed methods for breast cancer detection via numerical examples with data simulated using the finite-difference time-domain method based on a 3D realistic breast model.