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相控阵成像系统中用于相位像差校正的闭环机器学习算法。I. 算法合成与实验结果 [超声医学成像]

A closed loop ML algorithm for phase aberration correction in phased array imaging systems. I. Algorithm synthesis and experimental results [Ultrasound medical imaging].

作者信息

Fortes J P

机构信息

Pontificia Univ. Catolica do Rio de Janeiro.

出版信息

IEEE Trans Ultrason Ferroelectr Freq Control. 1997;44(2):259-70. doi: 10.1109/58.585111.

DOI:10.1109/58.585111
PMID:18244124
Abstract

A new closed loop algorithm is described, based on the maximum likelihood theory, that corrects phase aberrations in phased array coherent imaging systems using phase estimates which are directly obtained from measured data (and not from estimated correlation functions). It has the advantage of estimating phase differences with respect to the same reference, and not phase differences between signals in adjacent array elements, eliminating the need to perform an integration to get the phase aberration profile. It allows for a real time implementation, in the sense that corrected data flows out of the circuit at the same rate that input data is fed into it. Being a closed loop algorithm, it is able to track time variations that may occur in the phase aberrations and, as in any phase lock loop circuit, it shows a trade-off between acquisition time and phase jitter.

摘要

本文描述了一种基于最大似然理论的新型闭环算法,该算法利用直接从测量数据(而非估计的相关函数)获得的相位估计值,校正相控阵相干成像系统中的相位像差。它具有相对于同一参考估计相位差的优点,而不是估计相邻阵列元件中信号之间的相位差,从而无需进行积分来获得相位像差分布。从校正后的数据以与输入数据相同的速率流出电路的意义上来说,它允许实时实现。作为一种闭环算法,它能够跟踪相位像差中可能出现的时间变化,并且与任何锁相环电路一样,它在捕获时间和相位抖动之间表现出一种权衡。

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A closed loop ML algorithm for phase aberration correction in phased array imaging systems. I. Algorithm synthesis and experimental results [Ultrasound medical imaging].相控阵成像系统中用于相位像差校正的闭环机器学习算法。I. 算法合成与实验结果 [超声医学成像]
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