2020
Attenuation correction using deep Learning and integrated UTE/multi-echo Dixon sequence: evaluation in amyloid and tau PET imaging
Gong K, Han P, Johnson K, El Fakhri G, Ma C, Li Q. Attenuation correction using deep Learning and integrated UTE/multi-echo Dixon sequence: evaluation in amyloid and tau PET imaging. European Journal Of Nuclear Medicine And Molecular Imaging 2020, 48: 1351-1361. PMID: 33108475, PMCID: PMC8411350, DOI: 10.1007/s00259-020-05061-w.Peer-Reviewed Original ResearchConceptsAttenuation correctionResultsThe Dice coefficientPseudo-CT imagesMR-based AC methodsAccurate ACAC accuracyPET imagingDice coefficientQuantitative accuracyAtlas methodAC methodGradient echoNear verticesTau imagingTau PET imagingAlzheimer's diseaseUltrashortCorrectionTau pathologyRapid acquisitionDeep learning methodsMonitoring of Alzheimer’s diseasePET/MRAmyloid
2019
MR-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