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Comparison of Slot-based and Vivaldi Antennas for Breast Tumor Detection using Machine Learning and Microwave Imaging Algorithms

机译:采用机器学习和微波成像算法的槽基和Vivaldi天线对乳腺肿瘤检测的比较

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We compare the performance accuracy of a slot-based antenna and a Vivaldi antenna for breast tumor detection using machine learning (ML) algorithms jointly with microwave imaging (MWI) processing. MWI is known for having low resolution. Therefore, we here study the conjoint use of ML and MWI, in order to enable accurate detection of breast tumors and evaluate how the probing antenna affects the overall system performance. To this end, we perform measurements in the frequency range of 2–6 GHz on anthropomorphic breasts of different volumes and shapes, where we placed two types of tumors. The slot-based antenna provides better imaging results (i.e. good detection of the tumor), but the accuracy of ML techniques is only 60%. Concerning the Vivaldi antenna, the images present clutter, but the accuracy of ML techniques is as high as 85%. These results show that ML and MWI can be complementary to each other.
机译:我们使用与微波成像(MWI)加工共同使用机器学习(ML)算法来比较基于插槽的天线和Vivaldi天线的性能准确性和用于乳腺肿瘤的天线。 众所周知,MWI具有低分辨率。 因此,我们在这里研究了ML和MWI的联合使用,以便能够精确地检测乳腺肿瘤并评估探测天线如何影响整体系统性能。 为此,我们在不同体积和形状的拟人乳房上进行2-6 GHz的频率范围的测量,我们放置了两种类型的肿瘤。 基于槽的天线提供更好的成像结果(即良好的肿瘤检测),但ML技术的准确性仅为60%。 关于Vivaldi天线,图像呈现杂波,但ML技术的精度高达85%。 这些结果表明ML和MWI可以互相互补。

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