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首页> 外文期刊>IEEE Transactions on Biomedical Engineering >Ultrawideband microwave breast cancer detection: a detection-theoretic approach using the generalized likelihood ratio test
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Ultrawideband microwave breast cancer detection: a detection-theoretic approach using the generalized likelihood ratio test

机译：超宽带微波乳腺癌检测：使用广义似然比检验的检测理论方法

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摘要

Microwave imaging has been suggested as a promising modality for early-stage breast cancer detection. In this paper, we propose a statistical microwave imaging technique wherein a set of generalized likelihood ratio tests (GLRT) is applied to microwave backscatter data to determine the presence and location of strong scatterers such as malignant tumors in the breast. The GLRT is formulated assuming that the backscatter data is Gaussian distributed with known covariance matrix. We describe the method for estimating this covariance matrix offline and formulating a GLRT for several heterogeneous two-dimensional (2-D) numerical breast phantoms, several three-dimensional (3-D) experimental breast phantoms, and a 3-D numerical breast phantom with a realistic half-ellipsoid shape. Using the GLRT with the estimated covariance matrix and a threshold chosen to constrain the false discovery rate (FDR) of the image, we show the capability to detect and localize small (<0.6 cm) tumors in our numerical and experimental breast phantoms even when the dielectric contrast of the malignant-to-normal tissue is below 2:1.
机译：微波成像已被认为是早期乳腺癌检测的一种有前途的方式。在本文中，我们提出了一种统计微波成像技术，其中将一组广义似然比测试（GLRT）应用于微波反向散射数据，以确定强散射体（例如乳房中的恶性肿瘤）的存在和位置。 GLRT的公式是假设反向散射数据是高斯分布的，且具有已知的协方差矩阵。我们描述了离线估计此协方差矩阵并为几种异质二维（2-D）数值乳腺模型，几个三维（3-D）实验性乳腺模型和3-D数字乳腺模型制定GLRT的方法。具有逼真的半椭圆形。使用GLRT与估计的协方差矩阵和选择的阈值来约束图像的错误发现率（FDR），我们展示了能够在数字和实验性乳房幻像中检测和定位小的（<0.6 cm）肿瘤的能力，即使当恶性组织与正常组织的介电对比低于2：1。

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