Direct Extraction of Tumor Response Based on Ensemble Empirical Mode Decomposition for Image Reconstruction of Early Breast Cancer Detection by UWB

IF 3.8 2区 医学 Q2 ENGINEERING, BIOMEDICAL IEEE Transactions on Biomedical Circuits and Systems Pub Date : 2015-11-03 DOI:10.1109/TBCAS.2015.2481940
Qinwei Li, X. Xiao, Liang Wang, Hang Song, H. Kono, Peifang Liu, Hong Lu, T. Kikkawa
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引用次数: 47

Abstract

A direct extraction method of tumor response based on ensemble empirical mode decomposition (EEMD) is proposed for early breast cancer detection by ultra-wide band (UWB) microwave imaging. With this approach, the image reconstruction for the tumor detection can be realized with only extracted signals from as-detected waveforms. The calibration process executed in the previous research for obtaining reference waveforms which stand for signals detected from the tumor-free model is not required. The correctness of the method is testified by successfully detecting a 4 mm tumor located inside the glandular region in one breast model and by the model located at the interface between the gland and the fat, respectively. The reliability of the method is checked by distinguishing a tumor buried in the glandular tissue whose dielectric constant is 35. The feasibility of the method is confirmed by showing the correct tumor information in both simulation results and experimental results for the realistic 3-D printed breast phantom.
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基于集成经验模态分解的肿瘤反应直接提取UWB早期乳腺癌检测图像重建
提出了一种基于集成经验模态分解(EEMD)的肿瘤反应直接提取方法,用于超宽带(UWB)微波成像早期乳腺癌检测。利用该方法,仅从检测波形中提取信号即可实现用于肿瘤检测的图像重建。在以前的研究中,为了获得代表从无肿瘤模型检测到的信号的参考波形而进行的校准过程是不需要的。通过在一个乳腺模型中成功检测到一个位于腺区内的4mm肿瘤,以及在乳腺与脂肪交界处的模型,验证了该方法的正确性。通过区分介电常数为35的腺体组织中埋藏的肿瘤来检验该方法的可靠性。仿真结果和实验结果均显示了真实的3d打印乳腺假体的肿瘤信息,验证了该方法的可行性。
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来源期刊
IEEE Transactions on Biomedical Circuits and Systems
IEEE Transactions on Biomedical Circuits and Systems 工程技术-工程:电子与电气
CiteScore
10.00
自引率
13.70%
发文量
174
审稿时长
3 months
期刊介绍: The IEEE Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems Society to a wide variety of related areas such as: • Bioelectronics • Implantable and wearable electronics like cochlear and retinal prosthesis, motor control, etc. • Biotechnology sensor circuits, integrated systems, and networks • Micropower imaging technology • BioMEMS • Lab-on-chip Bio-nanotechnology • Organic Semiconductors • Biomedical Engineering • Genomics and Proteomics • Neuromorphic Engineering • Smart sensors • Low power micro- and nanoelectronics • Mixed-mode system-on-chip • Wireless technology • Gene circuits and molecular circuits • System biology • Brain science and engineering: such as neuro-informatics, neural prosthesis, cognitive engineering, brain computer interface • Healthcare: information technology for biomedical, epidemiology, and other related life science applications. General, theoretical, and application-oriented papers in the abovementioned technical areas with a Circuits and Systems perspective are encouraged to publish in TBioCAS. Of special interest are biomedical-oriented papers with a Circuits and Systems angle.
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