Kosmas P, Laranjeira S, Dixon J H, Li X, Chen Y
Division of Engineering and the Department of Informatics, King's College London, WC2R 2LS, UK.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:708-11. doi: 10.1109/IEMBS.2010.5626158.
This paper studies the decomposition of the time reversal operator (DORT, by the French acronym) technique for microwave breast lesion classification. We apply the finitedifference time-domain (FDTD) method to a realistic numerical breast phantom where lesion-like targets are artificially introduced, and obtain the multistatic data matrix (MDM) for a particular antenna array configuration. Then, the singular value decomposition (SVD) of this matrix is derived for different targets, which represent malignant and benign lesions. We show that the singular value spectrum can assist in classifying these targets as malignant or benign, especially in the case where contrast-enhanced agents can be employed to allow the analysis of differential backscatter data.
本文研究用于微波乳腺病变分类的时间反转算子分解（DORT，法语首字母缩写）技术。我们将时域有限差分（FDTD）方法应用于一个逼真的数字化乳腺模型，该模型中人工引入了类似病变的目标，并针对特定的天线阵列配置获取多静态数据矩阵（MDM）。然后，针对代表恶性和良性病变的不同目标，推导该矩阵的奇异值分解（SVD）。我们表明，奇异值谱有助于将这些目标分类为恶性或良性，特别是在可以使用对比增强剂来分析差分后向散射数据的情况下。
