Linked Life Data

19551128

Source:http://linkedlifedata.com/resource/pubmed/id/19551128

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
26
pubmed:dateCreated
2009-6-24
pubmed:abstractText
With the development of in-vivo free-space fluorescence molecular imaging and multi-modality imaging for small animals, there is a need for new reconstruction methods for real animal-shape models with a large dataset. In this paper we are reporting a novel hybrid adaptive finite element algorithm for fluorescence tomography reconstruction, based on a linear scheme. Two different inversion strategies (Conjugate Gradient and Landweber iterations) are separately applied to the first mesh level and the succeeding levels. The new algorithm was validated by numerical simulations of a 3-D mouse atlas, based on the latest free-space setup of fluorescence tomography with 360 degrees geometry projections. The reconstructed results suggest that we are able to achieve high computational efficiency and spatial resolution for models with irregular shape and inhomogeneous optical properties.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1094-4087
pubmed:author
pubmed:issnType
Electronic
pubmed:day
24
pubmed:volume
15
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
18300-17
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Reconstruction for free-space fluorescence tomography using a novel hybrid adaptive finite element algorithm.
pubmed:affiliation
Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't