基于皮肤表面反射和神经网络的微波乳房成像复介电常数重建

IF 3 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Peixian Zhu;Shouhei Kidera
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引用次数: 0

摘要

本文介绍了一种利用多层感知器(MLP)神经网络(NN)方法重建复杂介电常数剖面的实验验证方法,用于乳腺癌的定量微波识别。将MLP-NN与蒙皮表面抑制预处理相结合,可以实现从四维散射数据到复杂介电常数三维剖面的直接转换。实验数据由超宽带雷达设备使用简化的乳房幻影测量,验证了我们的方法即使在使用有限数量的训练数据集时也能提供复杂介电常数曲线的实部和虚部。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Complex Permittivity Reconstruction Using Skin Surface Reflection and Neural Network for Microwave Breast Imaging
This study introduces an experimental validation for the complex permittivity profile reconstruction using the multi-layer perceptron (MLP) neural network (NN) approach for quantitative microwave recognition of breast cancer. A direct conversion from the four-dimensional scattered data to the complex permittivity three-dimensional profile can be achieved by combining the MLP-NN and the skin surface rejection preprocessing. The experimental data, measured by ultra-wideband radar equipment using a simplified breast phantom, validates that our approach provides both the real and imaginary parts of complex permittivity profiles, even when using limited numbers of training datasets.
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来源期刊
CiteScore
5.80
自引率
9.40%
发文量
58
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