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Sparse Matrix Beamforming and Image Reconstruction for 2-D HIFU Monitoring Using Harmonic Motion Imaging for Focused Ultrasound (HMIFU) With In Vitro Validation

机译:二维HIFU监测的稀疏矩阵波束成形和图像重建,使用谐波运动成像技术对聚焦超声(HMIFU)进行体外验证

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Harmonic motion imaging for focused ultrasound (HMIFU) utilizes an amplitude-modulated HIFU beam to induce a localized focal oscillatory motion simultaneously estimated. The objective of this study is to develop and show the feasibility of a novel fast beamforming algorithm for image reconstruction using GPU-based sparse-matrix operation with real-time feedback. In this study, the algorithm was implemented onto a fully integrated, clinically relevant HMIFU system. A single divergent transmit beam was used while fast beamforming was implemented using a GPU-based delay-and-sum method and a sparse-matrix operation. Axial HMI displacements were then estimated from the RF signals using a 1-D normalized cross-correlation method and streamed to a graphic user interface with frame rates up to 15 Hz, a 100-fold increase compared to conventional CPU-based processing. The real-time feedback rate does not require interrupting the HIFU treatment. Results in phantom experiments showed reproducible HMI images and monitoring of 22 in vitro HIFU treatments using the new 2-D system demonstrated reproducible displacement imaging, and monitoring of 22 in vitro HIFU treatments using the new 2-D system showed a consistent average focal displacement decrease of 46.714.6% during lesion formation. Complementary focal temperature monitoring also indicated an average rate of displacement increase and decrease with focal temperature at , and , respectively. These results reinforce the HMIFU capability of estimating and monitoring stiffness related changes in real time. Current ongoing studies include clinical translation of the presented system for monitoring of HIFU treatment for breast and pancreatic tumor applications.
机译:聚焦超声的谐波运动成像(HMIFU)利用调幅HIFU光束来诱导同时估计的局部聚焦振荡运动。这项研究的目的是开发并展示一种新颖的快速波束形成算法,该算法使用基于GPU的具有实时反馈的稀疏矩阵运算进行图像重建的可行性。在这项研究中,该算法已在完全集成的,临床相关的HMIFU系统上实现。使用单个发散发射波束,同时使用基于GPU的延迟和求和方法和稀疏矩阵操作实现快速波束成形。然后,使用一维归一化互相关方法从RF信号估计轴向HMI位移,并将其传输到图形用户界面,其帧频高达15 Hz,与传统基于CPU的处理相比增加了100倍。实时反馈速率不需要中断HIFU处理。幻像实验的结果显示可重现的HMI图像,使用新的2-D系统对22种体外HIFU治疗进行监测可显示可重复的位移成像,对使用新的2-D系统的22种体外HIFU治疗进行监测可得出一致的平均焦距降低在病变形成过程中占46.714.6%。补充的焦点温度监测还表明,平均位移分别随,和处的焦点温度增加和减少。这些结果增强了HMIFU实时估计和监视刚度相关变化的能力。当前正在进行的研究包括所提出的系统的临床翻译,以监测用于乳腺癌和胰腺肿瘤应用的HIFU治疗。

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