Response to Comments on "Detection and Localization of Breast Cancer Using UWB Microwave Technology and CNN-LSTM Framework"

被引：0

作者：

Lu, Min ^{[1
]}

Xiao, Xia ^{[1
]}

Pang, Yanwei ^{[2
]}

Liu, Guancong ^{[1
]}

Lu, Hong ^{[3
]}

机构：

[1] Tianjin Univ, Sch Microelect, Tianjin Key Lab Imaging & Sensing Microelect Techn, Tianjin 300072, Peoples R China

[2] Tianjin Univ, Sch Elect & Informat Engn, Tianjin Key Lab Brain Inspired Intelligence Techno, Tianjin 300072, Peoples R China

[3] Tianjin Med Univ, Clin Res Ctr Canc s, Dept Breast Imaging, Natl Clin Res Canc,Canc Inst & Hosp, Tianjin&x2019, Tianjin, Peoples R China

来源：

IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES | 2023年 / 71卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Breast backscatter signals; convolutional neural network (CNN); long short-term memory (LSTM); tumor detection and localization;

D O I：

10.1109/TMTT.2023.3264555

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This article is a response to comments on the above article (Lu et al., 2022) by Reimer and Pistorius (2022) and Reimer et al. (2020). The discussion section of Lu et al. (2022) had cited and compared a relevant article (Al Khatib, Nov. 2021) regarding tumor detection and localization using the sizable experimental dataset (Reimer et al., 2020 and Breast backscatter signals, convolutional neural network (CNN) classifier, see "ref 20" in Table V of Lu et al. (2022). In addition, the diversity of the dataset broadens the data distribution, which is conducive to enhancing the network generalization performance. Our ongoing work will further enrich the dataset diversity by introducing the factor of the adipose shell as discussed by Reimer and Pistorius (2022), as well as other influencing factors, such as fibroglandular shape, and differences in dielectric properties. We appreciate Tyson Reimer and Dr. Stephen Pistorius for the careful comments on Lu et al. (2022).

引用

页码：4616 / 4616

页数：1

共 4 条

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[4]

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