2022
Joint spectral quantification of MR spectroscopic imaging using linear tangent space alignment‐based manifold learning
Ma C, Han P, Zhuo Y, Djebra Y, Marin T, Fakhri G. Joint spectral quantification of MR spectroscopic imaging using linear tangent space alignment‐based manifold learning. Magnetic Resonance In Medicine 2022, 89: 1297-1313. PMID: 36404676, PMCID: PMC9892363, DOI: 10.1002/mrm.29526.Peer-Reviewed Original ResearchConceptsSubspace-based methodsManifold learningIntrinsic low-dimensional structureGlobal coordinationLearning-based methodsNumerical simulation dataSpatial smoothness constraintSparsity constraintSpace alignmentSubspace modelSmoothness constraintSuperior performanceRoot mean square errorLinear transformationMechanical simulationsLow-dimensionalSquare errorSubspaceExperimental dataSpectroscopic imagingQuantum mechanical simulationsCoordinate alignmentMR spectroscopic imagingSpectral quantificationSimulated data
2017
Iterative Low-Dose CT Reconstruction With Priors Trained by Artificial Neural Network
Wu D, Kim K, Fakhri G, Li Q. Iterative Low-Dose CT Reconstruction With Priors Trained by Artificial Neural Network. IEEE Transactions On Medical Imaging 2017, 36: 2479-2486. PMID: 28922116, PMCID: PMC5897914, DOI: 10.1109/tmi.2017.2753138.Peer-Reviewed Original ResearchConceptsArtificial neural networkIterative reconstruction algorithmNeural networkLow-dose CT reconstructionReconstruction algorithmUnsupervised feature learningReconstructed imagesFeatures of imagesImprove reconstruction qualityNormal-dose imagesDecreasing radiation riskDevelopment of artificial neural networksFeature learningComplex featuresAuto-encoderReconstruction qualityData fidelityMachine learningSuppress noiseSmoothness constraintPhoton fluxPreservation abilityGrand ChallengeNoise reductionPriors