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通过高斯 - 牛顿迭代应用于散射积分方程的非微扰衍射层析成像。

Nonperturbative diffraction tomography via Gauss-Newton iteration applied to the scattering integral equation.

作者信息

Borup D T, Johnson S A, Kim W W, Berggren M J

机构信息

Department of Bioengineering, University of Utah, Salt Lake City 84112.

出版信息

Ultrason Imaging. 1992 Jan;14(1):69-85. doi: 10.1177/016173469201400105.

Abstract

A nonperturbational inverse scattering solution for the scattering integral equation (SIE) is presented. The numerical discretization of the SIE is performed by the moment method (MM) using sinc basis functions. Previous algorithms using the alternating variable (AV) nonlinear iteration with algebraic reconstruction technique (ART) solution of the linearizations are shown to diverge for high contrast/large size acoustic scatterers. This deficiency is alleviated by the use of the Gauss-Newton (GN) nonlinear iteration with conjugate gradient (CG) solution of the linearizations. Further numerical efficiency is attained by use of the biconjugate gradient (BCG) algorithm to solve the forward scattering problems. Test problem reconstructions of circular cylinders, using the Bessel series analytic solution to generate the scattering data, demonstrate the accuracy of the method. Inhomogeneous models of human cross-sections verify the high spatial resolution and high speed of sound contrast capability of the method.

摘要

提出了一种用于散射积分方程(SIE)的非微扰逆散射解。利用 sinc 基函数,通过矩量法(MM)对 SIE 进行数值离散化。先前使用交替变量(AV)非线性迭代和线性化代数重建技术(ART)解的算法,对于高对比度/大尺寸声学散射体显示出发散。通过使用高斯 - 牛顿(GN)非线性迭代和线性化共轭梯度(CG)解来缓解这一缺陷。通过使用双共轭梯度(BCG)算法解决正向散射问题,进一步提高了数值效率。使用贝塞尔级数解析解生成散射数据的圆柱测试问题重建验证了该方法的准确性。人体横截面的非均匀模型验证了该方法的高空间分辨率和高声速对比度能力。

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