Quick search Find article
Quick search
Find article

A comparison of truncated total least squares with Tikhonov regularization in imaging by ultrasound inverse scattering

Chao Liu1, Yuanmei Wang1 and Pheng Ann Heng2

Show affiliations


For good image quality using ultrasound inverse scattering, one alternately solves the well-posed forward scattering equation for an estimated total field and the ill-posed inverse scattering equation for the desired object property function. In estimating the total field, error or noise contaminates the coefficients of both matrix and data of the inverse scattering equation. Previous work on ill-posed inverse ultrasonic scattering commonly used Tikhonov regularization, which considers error only in the data. The solution so obtained is not precise enough to reconstruct the quantitative internal structure of a large or high-contrast object. This paper adopts the truncated total least squares method, simultaneously considering error and noise on both sides of the inverse scattering equation, and compares it with the classical Tikhonov regularization. We show that it can substantially improve reconstruction fit and image quality when the inverse scattering equation system is strongly ill-posed.


PACS

87.63.D- Ultrasonography

02.30.Zz Inverse problems

87.57.C- Image quality

02.70.Rr General statistical methods

02.60.-x Numerical approximation and analysis

87.57.N- Image analysis

MSC

65F10 Iterative methods for linear systems (See also 65N22)

93E24 Least squares and related methods

92C55 Biomedical imaging and signal processing (See also 44A12, 65R10)

Subjects

Mathematical physics

Computational physics

Medical physics

Dates

Issue 15 (7 August 2003)

Received 24 April 2003

Published 22 July 2003



View by subject




Export








Please login to access our web services, or create an account if you don't yet have one.

You must have cookies enabled in your web browser to be able to login.

Username
Password

Forgotten your password? Get a new one here.