DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jung, H | ko |
dc.contributor.author | Ye, Jong Chul | ko |
dc.contributor.author | Kim, EY | ko |
dc.date.accessioned | 2013-03-06T22:12:13Z | - |
dc.date.available | 2013-03-06T22:12:13Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2007-06 | - |
dc.identifier.citation | PHYSICS IN MEDICINE AND BIOLOGY, v.52, pp.3201 - 3226 | - |
dc.identifier.issn | 0031-9155 | - |
dc.identifier.uri | http://hdl.handle.net/10203/88646 | - |
dc.description.abstract | The dynamic MR imaging of time-varying objects, such as beating hearts or brain hemodynamics, requires a significant reduction of the data acquisition time without sacrificing spatial resolution. The classical approaches for this goal include parallel imaging, temporal filtering and their combinations. Recently, model-based reconstruction methods called k - t BLAST and k - t SENSE have been proposed which largely overcome the drawbacks of the conventional dynamic imaging methods without a priori knowledge of the spectral support. Another recent approach called k - t SPARSE also does not require exact knowledge of the spectral support. However, unlike k - t BLAST/SENSE, k - t SPARSE employs the so-called compressed sensing (CS) theory rather than using training. The main contribution of this paper is a new theory and algorithm that unifies the abovementioned approaches while overcoming their drawbacks. Specifically, we show that the celebrated k - t BLAST/SENSE are the special cases of our algorithm, which is asymptotically optimal from the CS theory perspective. Experimental results show that the new algorithm can successfully reconstruct a high resolution cardiac sequence and functional MRI data even from severely limited k - t samples, without incurring aliasing artifacts often observed in conventional methods. | - |
dc.language | English | - |
dc.publisher | IOP PUBLISHING LTD | - |
dc.subject | STATE FREE PRECESSION | - |
dc.subject | MINIMUM NORM ALGORITHM | - |
dc.subject | MAGNETIC-RESONANCE | - |
dc.subject | SIGNAL RECONSTRUCTION | - |
dc.subject | UNFOLD | - |
dc.subject | MRI | - |
dc.title | Improved k-t BLAST and k-t SENSE using FOCUSS | - |
dc.type | Article | - |
dc.identifier.wosid | 000246553500018 | - |
dc.identifier.scopusid | 2-s2.0-34248999153 | - |
dc.type.rims | ART | - |
dc.citation.volume | 52 | - |
dc.citation.beginningpage | 3201 | - |
dc.citation.endingpage | 3226 | - |
dc.citation.publicationname | PHYSICS IN MEDICINE AND BIOLOGY | - |
dc.identifier.doi | 10.1088/0031-9155/52/11/018 | - |
dc.contributor.localauthor | Ye, Jong Chul | - |
dc.contributor.nonIdAuthor | Jung, H | - |
dc.contributor.nonIdAuthor | Kim, EY | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordPlus | STATE FREE PRECESSION | - |
dc.subject.keywordPlus | MINIMUM NORM ALGORITHM | - |
dc.subject.keywordPlus | MAGNETIC-RESONANCE | - |
dc.subject.keywordPlus | SIGNAL RECONSTRUCTION | - |
dc.subject.keywordPlus | UNFOLD | - |
dc.subject.keywordPlus | MRI | - |
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