Document Detail

Unifying linear prior-information-driven methods for accelerated image acquisition.
MedLine Citation:
PMID:  11590640     Owner:  NLM     Status:  MEDLINE    
In the ongoing quest for faster imaging and higher spatial resolution, several methods have been developed to speed up data acquisition by incorporating prior information about the object being imaged. This study shows that many of these methods can be integrated into a single common equation. The unified framework provides a conceptual link that facilitates comparison among these methods to reveal their strengths and weaknesses. By considering the limitations of existing methods, a new member in this class of methods was developed. The broad-use linear acquisition speed-up technique (BLAST) uses the estimated amount of change within the FOV as prior information. BLAST has the flexibility of incorporating a variable amount of prior information to avoid the misleading appearance of "phantom features," which arise from overconstraining the reconstruction. Examples from dynamic imaging and MR thermometry are shown.
J Tsao; B Behnia; A G Webb
Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine     Volume:  46     ISSN:  0740-3194     ISO Abbreviation:  Magn Reson Med     Publication Date:  2001 Oct 
Date Detail:
Created Date:  2001-10-08     Completed Date:  2002-06-04     Revised Date:  2007-11-14    
Medline Journal Info:
Nlm Unique ID:  8505245     Medline TA:  Magn Reson Med     Country:  United States    
Other Details:
Languages:  eng     Pagination:  652-60     Citation Subset:  IM    
Copyright Information:
Copyright 2001 Wiley-Liss, Inc.
Biomedical Magnetic Resonance Laboratory, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
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MeSH Terms
Body Temperature
Face / anatomy & histology
Magnetic Resonance Imaging / methods*
Time Factors
Grant Support
5 P41 RR05964/RR/NCRR NIH HHS; R01 CA 51430/CA/NCI NIH HHS

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