2022
Virtual high‐count PET image generation using a deep learning method
Liu J, Ren S, Wang R, Mirian N, Tsai Y, Kulon M, Pucar D, Chen M, Liu C. Virtual high‐count PET image generation using a deep learning method. Medical Physics 2022, 49: 5830-5840. PMID: 35880541, PMCID: PMC9474624, DOI: 10.1002/mp.15867.Peer-Reviewed Original ResearchMeSH KeywordsDeep LearningHumansImage Processing, Computer-AssistedPositron-Emission TomographyResearch DesignSignal-To-Noise RatioConceptsStructural similarity indexImage quality evaluationDeep learning-based methodsDeep learning methodsImage qualityLearning-based methodsPET datasetsStatic datasetsDL methodsNet networkImage generationPET imagesNetwork inputsImage counterpartsLearning methodsNetwork outputTraining datasetPeak signalPositron emission tomography (PET) imagesQuality evaluationDatasetCross-validation resultsMean square errorHigh-count imagesImagesDeep learning–based attenuation correction for whole-body PET — a multi-tracer study with 18F-FDG, 68 Ga-DOTATATE, and 18F-Fluciclovine
Toyonaga T, Shao D, Shi L, Zhang J, Revilla EM, Menard D, Ankrah J, Hirata K, Chen MK, Onofrey JA, Lu Y. Deep learning–based attenuation correction for whole-body PET — a multi-tracer study with 18F-FDG, 68 Ga-DOTATATE, and 18F-Fluciclovine. European Journal Of Nuclear Medicine And Molecular Imaging 2022, 49: 3086-3097. PMID: 35277742, PMCID: PMC10725742, DOI: 10.1007/s00259-022-05748-2.Peer-Reviewed Original ResearchMeSH KeywordsDeep LearningFluorodeoxyglucose F18HumansImage Processing, Computer-AssistedNeoplasmsPositron Emission Tomography Computed TomographyPositron-Emission TomographyRadionuclide ImagingRadiopharmaceuticalsConceptsNeural networkNovel deep learningNet neural networkPET/CT datasetsImage analysis metricsPhysics-based loss functionDeep learningCT-derived attenuation mapAttenuation mapLoss functionAnalysis metricsDetail recoveryTumor volume estimationMLAACT datasetsOSEM algorithmNetworkAlgorithmAttenuation correctionCorrection framework
2021
Partial volume correction analysis for 11C-UCB-J PET studies of Alzheimer's disease
Lu Y, Toyonaga T, Naganawa M, Gallezot JD, Chen MK, Mecca AP, van Dyck CH, Carson RE. Partial volume correction analysis for 11C-UCB-J PET studies of Alzheimer's disease. NeuroImage 2021, 238: 118248. PMID: 34119639, PMCID: PMC8454285, DOI: 10.1016/j.neuroimage.2021.118248.Peer-Reviewed Original ResearchAlzheimer DiseaseBrainCerebrovascular CirculationHumansImage Processing, Computer-AssistedPositron-Emission TomographyRadiopharmaceuticals
2016
Determining the Minimal Required Radioactivity of 18F-FDG for Reliable Semiquantification in PET/CT Imaging: A Phantom Study
Chen MK, Menard DH, Cheng DW. Determining the Minimal Required Radioactivity of 18F-FDG for Reliable Semiquantification in PET/CT Imaging: A Phantom Study. Journal Of Nuclear Medicine Technology 2016, 44: 26-30. PMID: 26769598, DOI: 10.2967/jnmt.115.165258.Peer-Reviewed Original ResearchFluorodeoxyglucose F18Image Processing, Computer-AssistedPhantoms, ImagingPositron Emission Tomography Computed TomographyRadioactivity