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pubmed-article:12906256pubmed:dateCreated2003-8-8lld:pubmed
pubmed-article:12906256pubmed:abstractTextMany 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.lld:pubmed
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pubmed-article:12906256pubmed:authorpubmed-author:MadoreBrunoBlld:pubmed
pubmed-article:12906256pubmed:authorpubmed-author:LiangZhi-PeiZ...lld:pubmed
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pubmed-article:12906256pubmed:pagination1026-30lld:pubmed
pubmed-article:12906256pubmed:dateRevised2007-11-14lld:pubmed
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pubmed-article:12906256pubmed:year2003lld:pubmed
pubmed-article:12906256pubmed:articleTitleFast algorithms for GS-model-based image reconstruction in data-sharing Fourier imaging.lld:pubmed
pubmed-article:12906256pubmed:publicationTypeLetterlld:pubmed
pubmed-article:12906256pubmed:publicationTypeComparative Studylld:pubmed
pubmed-article:12906256pubmed:publicationTypeResearch Support, U.S. Gov't, P.H.S.lld:pubmed
pubmed-article:12906256pubmed:publicationTypeResearch Support, Non-U.S. Gov'tlld:pubmed
pubmed-article:12906256pubmed:publicationTypeEvaluation Studieslld:pubmed
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