An improved finite-element based reconstruction algorithm for fluorescence tomography

Xiaolei Song, Jing Bai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recently fluorescence tomography is developed as a promising way for non-invasive molecular-based imaging, especially for small animals. Based on a certain forward model with known optical properties, the distribution of fluorescence parameter could be estimated by proper inversion techniques. In this work, a novel fast inversion algorithm is applied to a linear scheme, which is generated by solving the diffusion equations with finite element method. The proposed reconstruction algorithm consists of a pre-iteration step executed off-line and an on-line post-processing step. In the off-line step the approximated value of generalized inverse is obtained by a iteration method of two-order expression. In the on-line step when the updated measurements come, a rough distribution of the required fluorescence parameter is firstly estimated by a matrix-vector multiplication, and then several steps of Landweber iteration are applied, which reduces the influence of the noisy measurements and integrates a priori knowledge about the unknown values. Numerical simulations of 2-D geometry model show that the algorithm could well estimate the spatial distribution of the fluorescent yield.

Original languageEnglish (US)
Title of host publicationProceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Pages761-765
Number of pages5
DOIs
StatePublished - Sep 25 2008
Event1st International Congress on Image and Signal Processing, CISP 2008 - Sanya, Hainan, China
Duration: May 27 2008May 30 2008

Publication series

NameProceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Volume3

Other

Other1st International Congress on Image and Signal Processing, CISP 2008
CountryChina
CitySanya, Hainan
Period5/27/085/30/08

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing

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