Linked Life Data

20707438

Source:http://linkedlifedata.com/resource/pubmed/id/20707438

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2010-8-16
pubmed:abstractText
The distorted Born iterative method (DBIM) computes iterative solutions to nonlinear inverse scattering problems through successive linear approximations. By decomposing the scattered field into a superposition of scattering by an inhomogeneous background and by a material perturbation, large or high-contrast variations in medium properties can be imaged through iterations that are each subject to the distorted Born approximation. However, the need to repeatedly compute forward solutions still imposes a very heavy computational burden. To ameliorate this problem, the multilevel fast multipole algorithm (MLFMA) has been applied as a forward solver within the DBIM. The MLFMA computes forward solutions in linear time for volumetric scatterers. The typically regular distribution and shape of scattering elements in the inverse scattering problem allow the method to take advantage of data redundancy and reduce the computational demands of the normally expensive MLFMA setup. Additional benefits are gained by employing Kaczmarz-like iterations, where partial measurements are used to accelerate convergence. Numerical results demonstrate both the efficiency of the forward solver and the successful application of the inverse method to imaging problems with dimensions in the neighborhood of ten wavelengths.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
1520-8524
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
128
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
679-90
pubmed:dateRevised
2011-8-3
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Fast inverse scattering solutions using the distorted Born iterative method and the multilevel fast multipole algorithm.
pubmed:affiliation
Department of Electrical and Computer Engineering, University of Rochester, Rochester, New York 14627, USA. hesford@ece.rochester.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, N.I.H., Extramural