Nonlinear multigrid algorithms for Bayesian optical diffusion tomography

Type of content
Journal Article
Thesis discipline
Degree name
Publisher
University of Canterbury. Electrical and Computer Engineering
Journal Title
Journal ISSN
Volume Title
Language
Date
2001
Authors
Ye, J.C.
Bouman, C.A.
Webb, K.J.
Millane, R.P.
Abstract

Optical diffusion tomography is a technique for imaging a highly scattering medium using measurements of transmitted modulated light. Reconstruction of the spatial distribution of the optical properties of the medium from such data is a difficult nonlinear inverse problem. Bayesian approaches are effective, but are computationally expensive, especially for three-dimensional (3-D) imaging. This paper presents a general nonlinear multigrid optimization technique suitable for reducing the computational burden in a range of nonquadratic optimization problems. This multigrid method is applied to compute the maximum a posteriori (MAP) estimate of the reconstructed image in the optical diffusion tomography problem. The proposed multigrid approach both dramatically reduces the required computation and improves the reconstructed image quality.

Description
Citation
Ye, J.C., Bouman, C.A., Webb, K.J., Millane, R.P. (2001) Nonlinear multigrid algorithms for Bayesian optical diffusion tomography. IEEE Trans. Image Processing, 10, pp. 909--922.
Keywords
Bayesian image reconstruction, multiresolution image reconstruction, nonlinear multigrid optimization, optical diffusion tomography
Ngā upoko tukutuku/Māori subject headings
ANZSRC fields of research
Rights
"©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE."