2015
Improved Low-Rank Filtering of Magnetic Resonance Spectroscopic Imaging Data Corrupted by Noise and <inline-formula><tex-math notation="LaTeX">$B_0$</tex-math></inline-formula> Field Inhomogeneity
Liu Y, Ma C, Clifford B, Lam F, Johnson C, Liang Z. Improved Low-Rank Filtering of Magnetic Resonance Spectroscopic Imaging Data Corrupted by Noise and$B_0$ Peer-Reviewed Original ResearchConceptsLow-rank filterSignal-to-noise ratioConstrained Cramer-RaoDenoising MRSI dataFiltering methodLow-rank modelCramer-RaoDenoising performanceRank minimizationHigh-resolution magnetic resonance spectroscopic imagingBoundary constraintsIn vivo MRSI dataData corruptionLow-rankMRSI dataFilterNoiseUpper boundB0 field inhomogeneityField inhomogeneity correctionDenoisingField inhomogeneityInhomogeneity correctionMethodMagnetic resonance spectroscopic imaging
2013
PERFORMANCE ANALYSIS OF DENOISING WITH LOW-RANK AND SPARSITY CONSTRAINTS
Lam F, Ma C, Liang Z. PERFORMANCE ANALYSIS OF DENOISING WITH LOW-RANK AND SPARSITY CONSTRAINTS. 2013, 1223-1226. DOI: 10.1109/isbi.2013.6556701.Peer-Reviewed Original ResearchLow-rankDenoising methodSparsity constraintLow-rank propertyNoise reductionConstrained Cramer-RaoImpressive empirical resultsDenoising effectDenoising capabilityDenoisingSparsityTheoretical boundsMaximum noise reductionCramer-RaoNumerical simulationsUpper boundImaging applicationsConstraintsEmpirical resultsBoundsNoiseMethodCapabilityImages