T2 mapping from highly undersampled data by reconstruction of principal component coefficient maps using compressed sensing

Magnetic Resonance in Medicine

Volumn 67, Issue 5, 2012, Pages 1355-1366

  Huang, Chuan ^a   Graff, Christian G ^b,d   Clarkson, Eric W ^b   Bilgin, Ali ^c   Altbach, Maria I ^b  

^a University of Arizona   (United States)

^b UNIVERSITY OF ARIZONA   (United States)

^c University of Arizona   (United States)

^d CENTER FOR DEVICES AND RADIOLOGICAL HEALTH   (United States)

Author keywords

compressed sensing; FSE; parameter mapping; principal component analysis

Indexed keywords

COMPRESSED SENSING; COST FUNCTIONS; MAPPING; PRINCIPAL COMPONENT ANALYSIS;

ACQUISITION TIME; ALGORITHM RECONSTRUCTION; ESTIMATES OF PARAMETERS; HIGH SPATIAL FREQUENCY; MODEL-BASED ALGORITHMS; MULTIPLE IMAGE; OPTIMIZATION PROBLEMS; PRINCIPAL COMPONENTS;

PARAMETER ESTIMATION;

ALGORITHM; ARTICLE; IMAGE RECONSTRUCTION; NUCLEAR MAGNETIC RESONANCE IMAGING; PHANTOM; PRINCIPAL COMPONENT ANALYSIS; COMPUTER ASSISTED DIAGNOSIS; HUMAN; IMAGE ENHANCEMENT; INFORMATION PROCESSING; METHODOLOGY; REPRODUCIBILITY; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING;

ALGORITHMS; DATA COMPRESSION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; PRINCIPAL COMPONENT ANALYSIS; REPRODUCIBILITY OF RESULTS; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84859719425     PISSN: 07403194     EISSN: 15222594     Source Type: Journal    
DOI: 10.1002/mrm.23128     Document Type: Article

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