2024
Adaptive Deep Image Prior Enhances Ultra-Low Dose PET Imaging with NeuroEXPLORER
Li A, Gravel P, Gallezot J, Toyonaga T, Fontaine K, Carson R, Tang J. Adaptive Deep Image Prior Enhances Ultra-Low Dose PET Imaging with NeuroEXPLORER. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10657691.Peer-Reviewed Original ResearchContrast recovery coefficientCounting imagingLearning-based denoising methodsHead motion correctionDeep Image PriorLow-dose imagesOptimal stopping iterationsDose imagesAttenuation mapBrain phantomDeep imagingFull-count dataImage priorsMotion correctionSignal-to-noise ratioDenoising methodSequence of outputsTraining dataPET imagingStopping iterationDecreased signal-to-noise ratioNoise ratioPost-processing techniquesReconstructed imagesRecovery coefficient
2013
Evaluation of motion correction methods in human brain PET imaging—A simulation study based on human motion data
Jin X, Mulnix T, Gallezot J, Carson RE. Evaluation of motion correction methods in human brain PET imaging—A simulation study based on human motion data. Medical Physics 2013, 40: 102503. PMID: 24089924, PMCID: PMC3785538, DOI: 10.1118/1.4819820.Peer-Reviewed Original ResearchConceptsAccurate motion dataMotion correction methodEvent motion correctionIntraframe motionCorrection methodMotion dataMotion correctionROI intensitiesHead motion dataImage reconstructionKinetic modelHuman motion dataSystem resolutionHead motionMotionSimulation studyFrame-based methodsPotential figuresKinetic parametersAccuracyMC methodAttenuation mapImage registrationHigh-contrast regionsImage intensity