Efficient standardization of clinical T2‐weighted images: Phase‐conjugacy e‐CAMP with projected gradient descent
Zhang H, Elsaid N, Sun H, Tagare H, Galiana G. Efficient standardization of clinical T2‐weighted images: Phase‐conjugacy e‐CAMP with projected gradient descent. Magnetic Resonance In Medicine 2024, 92: 2723-2733. PMID: 38988054, DOI: 10.1002/mrm.30214.Peer-Reviewed Original ResearchData fidelity termSignal evolution modelFidelity termGradient descentProjected GradientEfficient algorithmVirtual conjugate coilAlgorithmObjective functionMapping errorsTunable parametersLinear constraintsSampling schemeTSE dataLong echo train lengthMapsTrain lengthVirtualTurbo spin echoEcho train lengthHigh-resolutionSchemeDataBackground phaseError rangeConstrained alternating minimization for parameter mapping (CAMP)
Elsaid N, Dispenza N, Hu C, Peters D, Constable R, Tagare H, Galiana G. Constrained alternating minimization for parameter mapping (CAMP). Magnetic Resonance Imaging 2024, 110: 176-183. PMID: 38657714, PMCID: PMC11193090, DOI: 10.1016/j.mri.2024.04.029.Peer-Reviewed Original ResearchConceptsAlternating minimizationAccelerated parameter mappingImage qualityReconstructed image qualityEfficient reconstruction algorithmSacrificing model accuracyParameter mapsPhantom studyK-space samplingAcceleration datasetsK-spaceUndersampling artifactsCartesian acquisitionConsecutive imagesReconstruction algorithmIndividual imagesModel cost functionExponential decayEcho timeReconstruction methodCost functionReduce artifactsPhantomScan timeObjective function