2022
Unsupervised arterial spin labeling image superresolution via multiscale generative adversarial network
Cui J, Gong K, Han P, Liu H, Li Q. Unsupervised arterial spin labeling image superresolution via multiscale generative adversarial network. Medical Physics 2022, 49: 2373-2385. PMID: 35048390, DOI: 10.1002/mp.15468.Peer-Reviewed Original ResearchConceptsPeak signal-to-noise ratioStructural similarity indexNearest neighbor interpolationSignal-to-noise ratioTrilinear interpolationNeighbor interpolationAblation studiesB-spline interpolationLow-pass-filterLayer-by-layer trainingLoss termLow resolutionClearer structure boundariesLow signal-to-noise ratioIn vivo datasetsImage superresolutionGAN frameworkAdversarial networkB-spline interpolation methodReduce image noiseWeak labelsPrior informationSimilarity indexDipping methodSimulated data
2020
Motion correction for PET data using subspace-based real-time MR imaging in simultaneous PET/MR
Marin T, Djebra Y, Han P, Chemli Y, Bloch I, Fakhri G, Ouyang J, Petibon Y, Ma C. Motion correction for PET data using subspace-based real-time MR imaging in simultaneous PET/MR. Physics In Medicine And Biology 2020, 65: 235022. PMID: 33263317, PMCID: PMC7985095, DOI: 10.1088/1361-6560/abb31d.Peer-Reviewed Original ResearchConceptsPositron emission tomography reconstructionMotion-corrected PET reconstructionsPET reconstructionMotion-corrected PET imagesIrregular respiratory motionMotion fieldMotion correction methodMotion correction approachIrregular motion patternsUndersampled k-space dataImage quality of positron emission tomographyQuality of positron emission tomographyMotion patternsLow-rank characteristicsRespiratory motionContrast-to-noise ratioEstimated motion fieldSurrogate signalsMotion correctionK-space dataImage qualityReal-time MR imagingSimultaneous PET/MRMotion artifact reductionPET/MR scanners
2019
Body motion detection and correction in cardiac PET: Phantom and human studies
Sun T, Petibon Y, Han P, Ma C, Kim S, Alpert N, Fakhri G, Ouyang J. Body motion detection and correction in cardiac PET: Phantom and human studies. Medical Physics 2019, 46: 4898-4906. PMID: 31508827, PMCID: PMC6842053, DOI: 10.1002/mp.13815.Peer-Reviewed Original ResearchConceptsList-mode dataMotion-compensated image reconstructionMotion correctionCenter of massPET list-mode dataMotion correction methodMotion detectionMotion estimationImage reconstructionPatient body motionDegrade image qualityNonrigid registrationImage qualityMotion transformationCoincident distributionBody motion detectionCardiac positron emission tomographyBack-projection techniqueCovariance matrixImage volumesBody motionPositron emission tomographyBack-projectionReference framePhantomMR-based cardiac and respiratory motion correction of PET: application to static and dynamic cardiac 18F-FDG imaging
Petibon Y, Sun T, Han P, Ma C, Fakhri G, Ouyang J. MR-based cardiac and respiratory motion correction of PET: application to static and dynamic cardiac 18F-FDG imaging. Physics In Medicine And Biology 2019, 64: 195009. PMID: 31394518, PMCID: PMC7007962, DOI: 10.1088/1361-6560/ab39c2.Peer-Reviewed Original ResearchConceptsMR-based motion correctionRespiratory motion correctionMotion correctionImproved spatial resolutionReconstructed activity concentrationCardiac PET dataSpatial resolutionCoincidence eventsMR-basedPET imagingContrast-to-noise ratioCardiac PET imagingRespiratory phasesMC dataImprove image qualityMR acquisitionQuantitative accuracyCardiac PETPET dataActivity concentrationsMyocardium wallF-FDG PETDynamics studiesImage qualityMotion artifacts
2016
DC artifact correction for arbitrary phase-cycling sequence
Han P, Park H, Park S. DC artifact correction for arbitrary phase-cycling sequence. Magnetic Resonance Imaging 2016, 38: 21-26. PMID: 27998747, DOI: 10.1016/j.mri.2016.12.015.Peer-Reviewed Original Research