2023
Attenuation correction for PET imaging using conditional denoising diffusion probabilistic model
Dong Y, Jang S, Han P, Johnson K, Ma C, Fakhri G, Li Q, Gong K. Attenuation correction for PET imaging using conditional denoising diffusion probabilistic model. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338188.Peer-Reviewed Original ResearchDiffusion probabilistic modelGenerative adversarial networkConditional encodingAttenuation correctionDenoising diffusion probabilistic modelLow-level featuresProbabilistic modelAttenuation coefficientAdversarial networkExtract featuresPET/MR systemsEncodingPET acquisitionNovel methodDiffusion encodingMagnetic resonanceImagesPET imagingCorrectionMR imagingUNetAttenuationNetworkFeaturesResonance
2019
Performance evaluation of the 5‐Ring GE Discovery MI PET/CT system using the national electrical manufacturers association NU 2‐2012 Standard
Pan T, Einstein S, Kappadath S, Grogg K, Gomez C, Alessio A, Hunter W, Fakhri G, Kinahan P, Mawlawi O. Performance evaluation of the 5‐Ring GE Discovery MI PET/CT system using the national electrical manufacturers association NU 2‐2012 Standard. Medical Physics 2019, 46: 3025-3033. PMID: 31069816, PMCID: PMC7251507, DOI: 10.1002/mp.13576.Peer-Reviewed Original ResearchConceptsAxial field-of-viewPeak noise-equivalent count rateNoise-equivalent count rateField of viewCount ratePET performanceNational Electrical Manufacturers Association NU-2Transaxial field of viewPET/CT systemTime resolutionMean energy resolutionConventional photomultiplier tubesCount rate performanceImage quality phantomSpatial resolution measurementsFiltered back projection algorithmImage qualityEnergy resolutionAcquisition timeNU 2Count lossDetector designPhotomultiplier tubeMean energyPET/MR systems