2023
Unsupervised Deep Learning with Self-Validation in Dynamic PET Dose Reduction
Li A, Syed M, Naganawa M, Matuskery D, Carson R, Tang J. Unsupervised Deep Learning with Self-Validation in Dynamic PET Dose Reduction. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10337886.Peer-Reviewed Original ResearchNoise reductionSingle-frame methodsImage featuresImage framesTraining dataUnsupervised methodSpatiotemporal informationKinetic modelingDeep imageDynamic PETHard thresholdComposite imageBetter performanceImagesRobust performanceHigh noiseImaging dataFrame methodVast numberKinetic modeling analysisNoise levelFrameSelf-ValidationDynamic PET imagingCapability
2013
List-mode reconstruction for the FOCUS-220 with motion correction and spatially-variant probability density functions: Application to awake monkey imaging
Jin X, Jian Y, Mulnix T, Sandiego C, Yao R, Carson R. List-mode reconstruction for the FOCUS-220 with motion correction and spatially-variant probability density functions: Application to awake monkey imaging. 2011 IEEE Nuclear Science Symposium Conference Record 2013, 2985-2990. DOI: 10.1109/nssmic.2012.6551682.Peer-Reviewed Original ResearchEvent motion correctionIntra-frame motionMotion correctionMotion correction methodRadial offsetLarge motionEntire FOVFrame methodSpatial resolutionRadial resolutionProbability density functionCorrection methodTangential resolutionPoint sourcesMotionResolution kernelsHigh-quality imagesReconstruction algorithmList-mode reconstruction algorithmDensity functionList-mode reconstructionFOV