基于深度神经网络的改进全息微波乳房成像

Lulu Wang
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引用次数: 0

摘要

微波成像为乳腺癌的检测提供了极好的潜力。深度学习是生物医学成像领域的前沿技术,已成功应用于生物医学图像分类。研究了一种基于深度神经网络(DNN)的乳腺全息微波图像病灶识别方法。建立了一个计算机模型,在实际考虑下验证了所提出的方法。进行了各种实验来评估所提出的基于dnn的乳腺病变分类HMI。结果表明,该方法可以作为一种有用的成像工具,用于自动分类不同类型的乳腺组织。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Holographic Microwave Breast Imaging Based on Deep Neural Network
Microwave imaging offers excellent potential for breast cancer detection. Deep learning is state-of-the-art in biomedical imaging, which has been successfully applied for biomedical image classifications. This paper investigates a deep neural network (DNN) based classification method for identifying breast lesion in holographic microwave image (HMI). A computer model is developed to demonstrate the proposed method under practical consideration. Various experiments are carried out to evaluate the proposed DNN-based HMI for breast lesion classification. Results have shown that the proposed method could serve as a helpful imaging tool for automatically classifying different types of breast tissues.
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