Novel Multistatic Adaptive Microwave Imaging Methods for Early Breast Cancer Detection

August 3, 2011

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.

Hindawi Publishing Corporation
EURASIP Journal on Applied Signal Processing
Volume 2006 (2006), Article ID 91961, 13 pages
doi:10.1155/ASP/2006/91961

Accepted 21 December 2005

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.

This article was published in the special issue “Multisensor Processing for Signal Extraction and Applications” edited by Chong-Yung Chi, Ta-Sung Lee, Zhi-Quan Luo, Yue Wang, and Kung Yao.

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