Source reconstruction for spectrally-resolved bioluminescence tomography with sparse a priori information

Through restoration of the light source information in small animals in vivo, optical molecular imaging, such as fluorescence molecular tomography (FMT) and bioluminescence tomography (BLT), can depict biological and physiological changes observed using molecular probes. A priori information plays a...

Full description

Saved in:
Bibliographic Details
Published in:Optics express 2009-05, Vol.17 (10), p.8062-8080
Main Authors: Lu, Yujie, Zhang, Xiaoqun, Douraghy, Ali, Stout, David, Tian, Jie, Chan, Tony F, Chatziioannou, Arion F
Format: Article
Language:English
Subjects:
Animals
Computer Simulation
Green Fluorescent Proteins - metabolism
Luminescent Measurements - methods
Luminescent Proteins - metabolism
Mice
Monte Carlo Method
Phantoms, Imaging
Reproducibility of Results
Spectrum Analysis
Tomography - methods
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Through restoration of the light source information in small animals in vivo, optical molecular imaging, such as fluorescence molecular tomography (FMT) and bioluminescence tomography (BLT), can depict biological and physiological changes observed using molecular probes. A priori information plays an indispensable role in tomographic reconstruction. As a type of a priori information, the sparsity characteristic of the light source has not been sufficiently considered to date. In this paper, we introduce a compressed sensing method to develop a new tomographic algorithm for spectrally-resolved bioluminescence tomography. This method uses the nature of the source sparsity to improve the reconstruction quality with a regularization implementation. Based on verification of the inverse crime, the proposed algorithm is validated with Monte Carlo-based synthetic data and the popular Tikhonov regularization method. Testing with different noise levels and single/multiple source settings at different depths demonstrates the improved performance of this algorithm. Experimental reconstruction with a mouse-shaped phantom further shows the potential of the proposed algorithm.
ISSN:1094-4087
1094-4087
DOI:10.1364/OE.17.008062