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Empirical Assessment of Breast Lesion Detection Capability Through an Innovative Microwave Imaging Device

机译:通过创新的微波成像装置的乳房病变检测能力的经验评估

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This paper investigates the effect of conductivity weighting on microwave images obtained through a dedicated imaging device. MammoWave is a microwave imaging device for detection of breast lesions, operating using only two azimuthally rotating antennas without the use of matching liquids. For each breast, a set of conductivity weighted images are generated through modifying our algorithm based on Huygens principle, producing intensity maps representing the homogeneity of tissues’ dielectric properties. Subsequently, we introduce several imaging parameters (i.e. features) to quantify the non-homogenous behavior of the image. Through empirical investigation on 103 breasts, we can verify that a selection of these features could allow distinction between breasts with radiological findings (WF), i.e. with benign or malign lesions, and breasts with no radiological findings (NF). Statistical significance was set at p<0.05. We obtained single features Area Under the receiver operating characteristic Curves (AUCs) spanning from 0.65 to 0.68. Significantly, we achieve AUCs of up to 0.77 when considering dense breasts only, which tend to cause detection limitations in mammography exams.
机译:本文研究了电导率加权对通过专用成像装置获得的微波图像的影响。 Mammowave是一种用于检测乳房病变的微波成像装置,仅使用两个方方旋转天线操作而不使用匹配的液体。对于每个乳房,通过改变基于Huygens原理的算法来产生一组电导率加权图像,产生表示组织电介质特性的均匀性的强度图。随后,我们介绍几个成像参数(即功能)来量化图像的非同质行为。通过对103个乳房的经验研究,我们可以验证这些特征的选择可以允许区分具有放射性发现(WF)的乳房(即,具有良性或恶性病变,以及没有放射学发现的乳房(NF)。统计显着性设定为P <0.05。我们在接收器操作特性曲线(AUC)下获得单个特征区域,跨越0.65至0.68。显着,我们在考虑密集的乳房时,我们达到了高达0.77的AUC,这倾向于导致乳房检查中的检测限制。

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