Near Field UWB LCMV Imaging for Breast Cancer Detection with Entropy Based Artifacts Removal

In this paper, we propose a near field wideband linear constraint minimum variance (LCMV) beamforming with entropy based artifacts removal for UWB imaging in breast cancer detection. We define an entropy function in the antenna domain to measure the similarity of the different antenna signals and design a window function to eliminate the very similar artifacts at all antennas. This algorithm requires no prior knowledge about the breast and tumor, and brings no distortion to the tumor reflection. After removing the artifacts, we model the tumor as a near field region source. By applying the coherent signal subspace method, a wideband near field LCMV beamforming to the region source is developed. The output power of the beamforming forms the image of the breast with tumor embedded. Applied to 2D computed finite-difference time-domain (FDTD) data, the algorithm clearly identifies the 2 mm-diameter tumor. Simulation results also demonstrate the efficiency and robustness of the proposed algorithm