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Computational models of distributed aberration in ultrasound breast imaging

机译:超声乳腺成像中分布式像差的计算模型

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摘要

Two methods for simulation of ultrasound wavefront distortion are introduced and compared with aberration produced in simulations using digitized breast tissue specimens and a conventional multiple time-shift screen model. In the first method, aberrators are generated using a computational model of breast anatomy. In the second method, 10 to 12 irregularly shaped, strongly scattering inclusions are superimposed on the multiple-screen model to create a screen-inclusion model. Linear 2-D propagation of a 7.5-MHz planar, pulsed wavefront through each aberrator is computed using a first-order k-space method. The anatomical and screen-inclusion models reproduce two characteristics of arrival-time fluctuations observed in simulations using the digitized specimens that are not represented in simulations using the multiple-screen model: non-Gaussian first-order statistics and sharp changes in the rms arrival-time fluctuation as a function of propagation distance. The anatomical and screen-inclusion models both produce energy- level fluctuations similar to the digitized specimens, but the anatomical model more closely matches the pulse-shape distortion produced by the specimens. Both aberration models can readily be extended to 3-D, and the screen-inclusion model has the advantage of simplicity of implementation. Both models should enable more rigorous evaluation of adaptive focusing algorithms than is possible using conventional time-shift screen models.
机译:介绍了两种模拟超声波波前畸变的方法,并将其与使用数字化乳腺组织标本和传统的多重时移屏幕模型在模拟中产生的像差进行比较。在第一种方法中,使用乳房解剖结构的计算模型来生成畸变器。在第二种方法中,将10到12个不规则形状的强散射夹杂物叠加在多屏幕模型上,以创建一个屏幕包含模型。使用一阶k空间方法计算通过每个像差的7.5 MHz平面脉冲波前的线性二维传播。解剖模型和屏幕包含模型重现了使用数字化标本在模拟中观察到的到达时间波动的两个特征,这些特征在多屏幕模型的模拟中没有体现:非高斯一阶统计量和均方根到达率的急剧变化。时间波动与传播距离的关系。解剖模型和屏幕包含模型均会产生类似于数字化标本的能级波动,但解剖模型与标本所产生的脉冲形状失真更紧密匹配。两种像差模型都可以轻松扩展到3-D,并且屏幕包含模型具有易于实现的优点。与使用常规时移屏幕模型相比,这两种模型都应该能够对自适应聚焦算法进行更严格的评估。

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    was with, the Department of Electrical and Computer Engineering, University of Western Ontario, London, Ontario, Canada, and Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, Ontario, Canada;

    is now with the Diagnosis and Prevention Group, Defence Research and Development Canada, Toronto, Ontario, Canada.;

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