2024
Comparative analysis of two parametric imaging programs for NeuroEXPLORER studies
Zhang J, Gallezot J, Ye Q, Lu Y, Carson R. Comparative analysis of two parametric imaging programs for NeuroEXPLORER studies. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10655797.Peer-Reviewed Original ResearchAdaptive 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
2023
Markerless head motion tracking and event-by-event correction in brain PET
Zeng T, Lu Y, Jiang W, Zheng J, Zhang J, Gravel P, Wan Q, Fontaine K, Mulnix T, Jiang Y, Yang Z, Revilla E, Naganawa M, Toyonaga T, Henry S, Zhang X, Cao T, Hu L, Carson R. Markerless head motion tracking and event-by-event correction in brain PET. Physics In Medicine And Biology 2023, 68: 245019. PMID: 37983915, PMCID: PMC10713921, DOI: 10.1088/1361-6560/ad0e37.Peer-Reviewed Original ResearchConceptsPoint source studyHead motion correctionSmaller residual displacementMotion correctionIterative closest point (ICP) registration algorithmHead motion trackingSpatial resolutionResidual displacementData-driven evaluation methodHigh spatial resolutionLow noiseMotion trackingStereovision cameraMotion tracking deviceStructured lightEvent correctionBrain positron emission tomography (PET) imagingTracking deviceReconstruction resultsHMT methodPoint cloudsNegative biasReference cloudUMTEvaluation method