用于早期乳腺癌检测的多静态自适应微波成像

Multistatic adaptive microwave imaging for early breast cancer detection.

作者信息

Xie Yao, Guo Bin, Xu Luzhou, Li Jian, Stoica Petre

机构信息

Department of Electrical and Computer Engineering, University of Florida, Gainesville 32611, USA.

出版信息

IEEE Trans Biomed Eng. 2006 Aug;53(8):1647-57. doi: 10.1109/TBME.2006.878058.

DOI:10.1109/TBME.2006.878058

PMID:16916099

Abstract

We propose a new multistatic adaptive microwave imaging (MAMI) method for early breast cancer detection. MAMI is a two-stage robust Capon beamforming (RCB) based image formation algorithm. MAMI exhibits higher resolution, lower sidelobes, and better noise and interference rejection capabilities than the existing approaches. The effectiveness of using MAMI for breast cancer detection is demonstrated via a simulated 3-D breast model and several numerical examples.

摘要

我们提出了一种用于早期乳腺癌检测的新型多静态自适应微波成像（MAMI）方法。MAMI是一种基于稳健Capon波束形成（RCB）的两阶段图像形成算法。与现有方法相比，MAMI具有更高的分辨率、更低的旁瓣以及更好的噪声和干扰抑制能力。通过模拟三维乳腺模型和几个数值示例证明了使用MAMI进行乳腺癌检测的有效性。