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Proceedings Paper

Adaptive truncated total least square on distorted born iterative method in ultrasound inverse scattering problem
Author(s): Anita Carević; Xingzhao Yun; Mohamed Almekkawy
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Paper Abstract

One of the most powerful approach in ultrasound tomography (UT) is making use of distorted Born iterative (DBI) method to reconstruct high quality image in order to help locate and identify tumors more precisely. Due to its iterative nature, it begins with Born approximation as the initial guess. Then, it makes use of the inhomogeneous Greens function, as the kernel function, to alternatively calculate the total field for the forward problem and the scattering function for the inverse problem. One principal computational problem involved is that inverse problem is ill-posed, which will result in divergence of the DBI method if inappropriate regularization is used. This paper presents the regularization with truncated total least square (TTLS) where the adaptive algorithm is used to choose the regularization parameter in each iteration of DBI instead of using a fixed truncated value in all the iterations. In order to prevent the solution from being contaminated by noise, adaptive algorithm truncates the smallest singular values while minimizing the loss of signal obtained from transducers. Numerical simulations demonstrate that the proposed adaptive algorithm in conjunction with TTLS outperform TTLS with fixed truncation parameter by effectively reducing the noise and minimizing the relative error.

Paper Details

Date Published: 15 March 2019
PDF: 8 pages
Proc. SPIE 10955, Medical Imaging 2019: Ultrasonic Imaging and Tomography, 1095515 (15 March 2019); doi: 10.1117/12.2512416
Show Author Affiliations
Anita Carević, Univ. of Split (Croatia)
Xingzhao Yun, The Pennsylvania State Univ. (United States)
Mohamed Almekkawy, The Pennsylvania State Univ. (United States)

Published in SPIE Proceedings Vol. 10955:
Medical Imaging 2019: Ultrasonic Imaging and Tomography
Brett C. Byram; Nicole V. Ruiter, Editor(s)

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