Naslov
Adaptive truncated total least square on distorted born iterative method in ultrasound inverse scattering problem

Autori
Carević, Anita ; Yun, Xingzhao ; Almekkawy, Mohamed

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings Volume 10955, Medical Imaging 2019: Ultrasonic Imaging and Tomography / Brett C. Byram, Nicole V. Ruiter - San Diego (CA) : SPIE, 2019, 1095515-1095521

Skup
SPIE Medical Imaging 2019

Mjesto i datum
San Diego (CA), Sjedinjene Američke Države, 16.02.2019. - 21.02.2019

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Inverse problem, regularization, ultrasound tomography, distorted Born iterative method, Truncated total least squares

Sažetak
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 eld 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 fi xed 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.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Računarstvo

POVEZANOST RADA