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使用最小均方误差(LMSE)滤波器和中值滤波器进行超声衰减估计。

Ultrasound attenuation estimation using the LMSE filters and the median filter.

作者信息

Jang H S, Lee M H, Park S B

机构信息

Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Seoul.

出版信息

Ultrasound Med Biol. 1988;14(1):51-8. doi: 10.1016/0301-5629(88)90163-9.

Abstract

The ultrasound attenuation coefficient in known to increase with frequency in soft biological tissue within the diagnostic frequency range. The frequency dependent attenuation coefficient is an important parameter in clinical tissue characterization, especially in liver, and in ultrasonic quantitative B-scan imaging. But, because of the random spatial variation in the backscattered signal amplitude, the estimator variance becomes very large, making it difficult to estimate the attenuation slope from the backscattered ultrasound signal. In this paper we suggest a new ultrasound attenuation estimator based on the calibrated log spectral difference. The proposed estimation process consists of Wiener filtering, Kalman filtering, and median filtering in this order. The simulation results and experimental results with tissue equivalent (TE) phantoms show that combination of the above filterings yields a considerably reduced estimator variance compared with the conventional estimators.

摘要

已知在诊断频率范围内,软组织中的超声衰减系数会随频率增加。频率相关的衰减系数是临床组织表征中的一个重要参数,尤其是在肝脏以及超声定量B扫描成像中。但是,由于后向散射信号幅度存在随机空间变化,估计器方差变得非常大,这使得从后向散射超声信号估计衰减斜率变得困难。在本文中,我们提出了一种基于校准对数谱差的新型超声衰减估计器。所提出的估计过程依次包括维纳滤波、卡尔曼滤波和中值滤波。使用组织等效(TE)体模的模拟结果和实验结果表明,与传统估计器相比,上述滤波的组合可显著降低估计器方差。

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