2019
Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning
Gong K, Han P, Fakhri G, Ma C, Li Q. Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning. NMR In Biomedicine 2019, 35: e4224. PMID: 31865615, PMCID: PMC7306418, DOI: 10.1002/nbm.4224.Peer-Reviewed Original ResearchMeSH KeywordsBrainDeep LearningHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingSignal-To-Noise RatioSpin LabelsConceptsSignal-to-noise ratioImage denoisingReconstruction frameworkDeep learning-based image denoisingDeep learning-based denoisersMR image denoisingLearning-based denoisingLow signal-to-noise ratioK-space dataNoisy imagesTraining labelsTraining pairsNetwork inputNeural networkDenoisingIn vivo experiment dataSuperior performanceImaging speedReconstruction processImage qualityLong imaging timesNetworkFrameworkImagesSpatial resolution
2018
SERIAL transmit – parallel receive (STxPRx) MR imaging produces acceptable proton image uniformity without compromising field of view or SAR guidelines for human neuroimaging at 9.4 Tesla
Thulborn K, Ma C, Sun C, Atkinson I, Claiborne T, Umathum R, Wright S, Liang Z. SERIAL transmit – parallel receive (STxPRx) MR imaging produces acceptable proton image uniformity without compromising field of view or SAR guidelines for human neuroimaging at 9.4 Tesla. Journal Of Magnetic Resonance 2018, 293: 145-153. PMID: 30012280, PMCID: PMC6084804, DOI: 10.1016/j.jmr.2018.05.009.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBrainElectromagnetic FieldsHeadHumansMagnetic Resonance ImagingNeuroimagingPhantoms, ImagingProtonsSignal-To-Noise RatioConceptsProton MR imagesMR images of human brainArrays of surface coilsImages of human brainSurface coil arrayHuman brain imagingImage uniformityField of viewExcitation profilesSAR guidelinesBirdcage coilFLASH pulse sequenceSensitivity correctionSodium MR imagingPulse sequenceAcceptable uniformityCoil arrayExcitationSignal-to-noiseProtonHigh-resolution imagesSurface coilParallel receiverCoilMR imaging
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 Field Inhomogeneity. IEEE Transactions On Biomedical Engineering 2015, 63: 841-849. PMID: 26353360, DOI: 10.1109/tbme.2015.2476499.$B_0$ Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBrainHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingSignal Processing, Computer-AssistedSignal-To-Noise RatioConceptsLow-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
2014
Improved Image Reconstruction for Subspace-Based Spectroscopic Imaging Using Non-Quadratic Regularization
Wu Z, Lam F, Ma C, Liang Z. Improved Image Reconstruction for Subspace-Based Spectroscopic Imaging Using Non-Quadratic Regularization. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2014, 2014: 2432-2435. PMID: 25570481, DOI: 10.1109/embc.2014.6944113.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsComputer SimulationImage Processing, Computer-AssistedMagnetic Resonance SpectroscopyPhantoms, ImagingSignal-To-Noise RatioConceptsImage reconstructionLow-rank modelNon-quadratic regularizationHigh-resolution metabolic imagingSparsely sampled datasetsCapabilities of SPICESPICE frameworkOptimization problemPrimal-dualNon-quadraticImagesSNRAlgorithmDatasetPhantom studySparsenessSpectroscopic imaging methodReconstructionSpectroscopic imagingOptimizationRegularizationMethodCapabilityField-Inhomogeneity-Corrected Low-Rank Filtering of Magnetic Resonance Spectroscopic Imaging Data
Liu Y, Ma C, Clifford B, Lam F, Johnson C, Liang Z. Field-Inhomogeneity-Corrected Low-Rank Filtering of Magnetic Resonance Spectroscopic Imaging Data. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2014, 2014: 6422-6425. PMID: 25571466, DOI: 10.1109/embc.2014.6945098.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsHumansMagnetic Resonance SpectroscopyNeuroimagingSignal Processing, Computer-AssistedSignal-To-Noise RatioSoftware