Timing‐synchronized passive ultrasound imaging of cavitation using eigenspace‐based minimum variance beamforming and principal component analysis

波束赋形 主成分分析 传感器 计算机科学 空化 最小方差无偏估计量 算法 声学 数学 物理 人工智能 均方误差 电信 统计
作者
Shukuan Lu,Ruibo Su,Yezi Ma,Mingxi Wan
出处
期刊:Medical Physics [Wiley]
标识
DOI:10.1002/mp.17853
摘要

Abstract Background Passive ultrasound imaging (PUI) allows to spatially resolve cavitation triggered during ultrasound irradiation, its application in therapeutic ultrasound has been gaining attention in recent years. The diffraction mode of the imaging transducer greatly limits the PUI axial resolution, which can be improved by transmit‐receive synchronization and employment of delay sum beamforming (DSB) when transmitting short pulses, however, DSB yields poor performance in resolution and anti‐interference. Purpose Inspired by adaptive beamforming and its low‐complexity algorithm in active imaging field, this paper aims to develop an improved timing‐synchronized PUI (TSPUI) algorithm for detection of short‐pulse transmission‐induced cavitation. Methods The passive array data collected by timing synchronization is processed by minimum variance beamforming (MVB), whose weights are optimized by projection on the eigendecomposed signal subspace, that is, eigenspace‐based MVB (EMVB), with the sum of the flight times on the transmitting and receiving paths as the delay. Applying principal component analysis (PCA) on the pre‐collected MVB weight samples, a conversion matrix is constructed to allow the matrix inversion and eigendecomposition involved in weight calculation to be performed in a low dimension. The algorithm performance is confirmed by experiments, where a high‐intensity focused ultrasound transducer and a linear‐array transducer configured in a common parallel or vertical manner are employed for cavitation induction and cavitation imaging, and evaluated with the established indicators. Results Reducing the eigenvalue threshold coefficient allows more sidelobes to be removed, and choosing an appropriate principal component number can reduce the time cost while guaranteeing the reconstruction quality. EMVB‐PCA provides high resolution and anti‐interference performance relative to DSB, with a reduction of over 60% in the point spread area and over 14 dB in the sidelobe and noise level, meanwhile, its time cost is considerably lower than EMVB, with a reduction of over 80%. Additionally, constructing the conversion matrix by simulation is feasible and valid, providing convenience for real imaging. Conclusions EMVB‐PCA allows for high‐quality TSPUI reconstruction of cavitation at a fast rate, providing an effective tool for detecting short‐duration cavitation and further benefiting short‐pulse therapeutic ultrasound applications.
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