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Critical Reviews™ in Biomedical Engineering
SJR: 0.26 SNIP: 0.375 CiteScore™: 1.4

ISSN Imprimir: 0278-940X
ISSN En Línea: 1943-619X

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Critical Reviews™ in Biomedical Engineering

DOI: 10.1615/CritRevBiomedEng.2020033670
pages 85-93

Microwave-Induced Thermal Lesion Detection via Ultrasonic Scatterer Center Frequency Analysis with Autoregressive Cepstrum

Lei Sheng
Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, China
Wei Rao
Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, 29 Zhongguancun East Road, Haidian District, Beijing, 100190, PR China
Zhuhuang Zhou
College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China
Shuicai Wu
College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China
Guolin Ma
Department of Radiology, China-Japan Friendship Hospital, Beijing, China


We proposed a new method for microwave-induced thermal lesion detection using the autoregressive spectrum analysis of ultrasonic backscattered signals in this paper. Eighteen cases of microwave ablation experiments and twenty cases of water bath heating experiments were conducted. Ultrasonic radiofrequency data of normal and coagulated porcine liver tissues were collected through these two experiments. Then, autoregressive spectrum analysis was performed; the mean frequency of the dominant peak in the autoregressive spectrum was computed based on water bath experiments; and a method for recognizing normal and solidified tissues was obtained by comparing the difference of the dominant peak in the autoregressive spectrum. Two bandpass finite impulse response filters, whose passbands corresponded respectively to the dominant peak in the autoregressive spectrum of normal and coagulated tissues, were used to compute the power spectral integration for the microwave-induced experiments. Microwave-induced thermal lesions were detected based on the differences between the power spectral integrations from the two filters. Compared to the caliper-measured area, the power spectral integration detected area had an error of (10.25 ± 3.59). Experimental results indicated that the proposed method may be used in preliminary detection of microwave-induced thermal lesions.


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