Linked Life Data

18383297

Source:http://linkedlifedata.com/resource/pubmed/id/18383297

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2008-4-3
pubmed:abstractText
Noise is a major concern in many important imaging applications. To improve data signal-to-noise ratio (SNR), experiments often focus on collecting low-frequency k-space data. This article proposes a new scheme to enable extended k-space sampling in these contexts. It is shown that the degradation in SNR associated with extended sampling can be effectively mitigated by using statistical modeling in concert with anatomical prior information. The method represents a significant departure from most existing anatomically constrained imaging methods, which rely on anatomical information to achieve super-resolution. The method has the advantage that less accurate anatomical information is required relative to super-resolution approaches. Theoretical and experimental results are provided to characterize the performance of the proposed scheme.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0740-3194
pubmed:author
pubmed:issnType
Print
pubmed:volume
59
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
810-8
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Anatomically constrained reconstruction from noisy data.
pubmed:affiliation
Department of Electrical and Computer Engineering, University of Illinois, Urbana, Illinois 61801, USA. haldar@uiuc.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, N.I.H., Extramural