Nakagami分布
微波消融
超声波
计算机科学
接收机工作特性
微波成像
生物医学工程
人工智能
物理
核医学
烧蚀
微波食品加热
算法
医学
声学
机器学习
电信
解码方法
衰退
内科学
作者
Guang Yang,Siyuan Zhang,Xiejing Li,Ting Shen,Xin Jia,Yunjie Ding,Bo Zhang,Hua Wang,Xiaopeng Li,Pengyu Ren
出处
期刊:IEEE Transactions on Instrumentation and Measurement
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:: 1-1
标识
DOI:10.1109/tim.2023.3267375
摘要
Many quantitative ultrasound imaging techniques based on tissue properties have been established to ensure the safety and efficacy of thermal ablation treatment. However, which quantitative ultrasound imaging technique has superior monitoring properties has not yet been revealed. In this study, we investigated and compared the performance of envelope data distribution-dependent ultrasonic Nakagami, envelope data distribution-independent horizontally normalized Shannon entropy (hNSE), and differential attenuation coefficient intercept (DACI) based on frequency domain imaging technique during liver thermal ablation treatments. Quantitative ultrasound parameter images were constructed simultaneously from radiofrequency (RF) data collected during the process of microwave ablation (MWA) treatments in ex vivo and in vivo porcine livers. Contrast-to-noise ratios (CNR) were calculated to evaluate the contrast resolution of different imaging techniques. The mean CNR value of hNSE images was 6.06 ± 2.34 dB, being significantly higher than that of Nakagami images ( p <0.05, statistical) and DACI images ( p <0.05, statistical). Furthermore, the receiver operating characteristic (ROC) was used to evaluate the thermal lesion detection ability. The area under the curve (AUC) of B-mode, Nakagami, hNSE and DACI was 0.823, 0.839, 0.86 and 0.825, respectively. Additionally, our data analysis exhibited that hNSE has the excellent property of ablation area detections in the present study, whose correlation coefficient is 0.91. In conclusion, our study suggests that hNSE imaging, which does not require the specific data distribution has the best performance in thermal ablation detections and is a promising imaging method for further clinical research and application.
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