Regularized total least squares reconstruction for optical tomographic imaging using conjugate gradient method

Author

Zhu, Wenwu ; Wang, Yao ; Galatsanos, Nikolas P. ; Zhang, Jun

Author_Institution

Dept. of Electr. Eng., Polytech. Univ., Brooklyn, NY, USA

Volume

1

fYear

1997

fDate

26-29 Oct 1997

Firstpage

192

Abstract

A regularized total least square (RTLS) approach to solve a linear perturbation equation encountered in optical tomography is developed based on the Rayleigh quotient formulation. To compute efficiently the solution, the Rayleigh quotient form of the RTLS filter (RQF-RTLS) is used and a conjugate gradient algorithm is implemented. Simulation results show that the RQF-RTLS method obtains more stable and accurate solutions than the regularized least squares (RLS) approach which does not account for the errors in the operator

Keywords

conjugate gradient methods; diagnostic radiography; image reconstruction; least squares approximations; medical image processing; numerical stability; optical tomography; RQF-RTLS; RQF-RTLS method; RTLS filter; Rayleigh quotient formulation; accurate solution; conjugate gradient algorithm; conjugate gradient method; linear perturbation equation; medical optical imaging; operator errors; optical tomographic imaging; optical tomography; regularized least squares; regularized total least squares reconstruction; simulation results; stable solution; Equations; Image reconstruction; Least squares methods; Nonlinear optics; Optical filters; Optical imaging; Optical scattering; Rayleigh scattering; Resonance light scattering; Tomography;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1997. Proceedings., International Conference on

Conference_Location

Santa Barbara, CA

Print_ISBN

0-8186-8183-7

Type

conf

DOI

10.1109/ICIP.1997.647444

Filename

647444