Linked Life Data

19770900

Source:http://linkedlifedata.com/resource/pubmed/id/19770900

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
19
pubmed:dateCreated
2009-9-22
pubmed:abstractText
Bioluminescence tomography (BLT) poses a typical ill-posed inverse problem with a large number of unknowns and a relatively limited number of boundary measurements. It is indispensable to incorporate a priori information into the inverse problem formulation in order to obtain viable solutions. In the paper, Bayesian approach has been firstly suggested to incorporate multiple types of a priori information for BLT reconstruction. Meanwhile, a generalized adaptive Gaussian Markov random field (GAGMRF) prior model for unknown source density estimation is developed to further reduce the ill-posedness of BLT on the basis of finite element analysis. Then the distribution of bioluminescent source can be acquired by maximizing the log posterior probability with respect to a noise parameter and the unknown source density. Furthermore, the use of finite element method makes the algorithm appropriate for complex heterogeneous phantom. The algorithm was validated by numerical simulation of a 3-D micro-CT mouse atlas and physical phantom experiment. The reconstructed results suggest that we are able to achieve high computational efficiency and accurate localization of bioluminescent source.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1094-4087
pubmed:author
pubmed:issnType
Electronic
pubmed:day
14
pubmed:volume
17
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
16834-48
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Three-dimensional bioluminescence tomography based on Bayesian approach.
pubmed:affiliation
The College of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100190, China.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't