Linked Life Data

12906256

Source:http://linkedlifedata.com/resource/pubmed/id/12906256

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
2003-8-8
pubmed:abstractText
Many imaging experiments involve acquiring a time series of images. To improve imaging speed, several "data-sharing" methods have been proposed, which collect one (or a few) high-resolution reference(s) and a sequence of reduced data sets. In image reconstruction, two methods, known as "Keyhole" and reduced-encoding imaging by generalized-series reconstruction (RIGR), have been used. Keyhole fills in the unmeasured high-frequency data simply with those from the reference data set(s), whereas RIGR recovers the unmeasured data using a generalized series (GS) model, of which the basis functions are constructed based on the reference image(s). This correspondence presents a fast algorithm (and two extensions) for GS-based image reconstruction. The proposed algorithms have the same computational complexity as the Keyhole algorithm, but are more capable of capturing high-resolution dynamic signal changes.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0278-0062
pubmed:author
pubmed:issnType
Print
pubmed:volume
22
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1026-30
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Fast algorithms for GS-model-based image reconstruction in data-sharing Fourier imaging.
pubmed:publicationType
Letter, Comparative Study, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't, Evaluation Studies, Validation Studies