2023
FedFTN: Personalized federated learning with deep feature transformation network for multi-institutional low-count PET denoising
Zhou B, Xie H, Liu Q, Chen X, Guo X, Feng Z, Hou J, Zhou S, Li B, Rominger A, Shi K, Duncan J, Liu C. FedFTN: Personalized federated learning with deep feature transformation network for multi-institutional low-count PET denoising. Medical Image Analysis 2023, 90: 102993. PMID: 37827110, PMCID: PMC10611438, DOI: 10.1016/j.media.2023.102993.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsHumansImage Processing, Computer-AssistedPositron-Emission TomographySignal-To-Noise RatioConceptsFederated learning processFederated learning algorithmFederated learning strategyLarge domain shiftDifferent data distributionsTransformation networkLarge-scale datasetsDeep learningDomain shiftLearning algorithmDownstream tasksNetwork weightsFeature outputFeature transformationSecurity concernsData distributionCollaborative trainingPersonalized modelPET image qualityReconstructed imagesReconstruction methodImage qualityNetworkEfficient wayLocal data
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 imagesImagesA personalized deep learning denoising strategy for low-count PET images
Liu Q, Liu H, Mirian N, Ren S, Viswanath V, Karp J, Surti S, Liu C. A personalized deep learning denoising strategy for low-count PET images. Physics In Medicine And Biology 2022, 67: 145014. PMID: 35697017, PMCID: PMC9321225, DOI: 10.1088/1361-6560/ac783d.Peer-Reviewed Original Research
2021
Artificial Intelligence-Based Image Enhancement in PET Imaging Noise Reduction and Resolution Enhancement
Liu J, Malekzadeh M, Mirian N, Song TA, Liu C, Dutta J. Artificial Intelligence-Based Image Enhancement in PET Imaging Noise Reduction and Resolution Enhancement. PET Clinics 2021, 16: 553-576. PMID: 34537130, PMCID: PMC8457531, DOI: 10.1016/j.cpet.2021.06.005.Peer-Reviewed Original ResearchMeSH KeywordsArtificial IntelligenceHumansImage EnhancementImage Processing, Computer-AssistedPositron-Emission TomographySignal-To-Noise RatioConceptsArtificial intelligence modelsImage enhancementIntelligence modelsArtificial intelligenceNetwork architectureEvaluation metricsLarge-scale adoptionData typesImage denoisingLoss functionPET imagesLow spatial resolutionHigh noiseResolution enhancementImagesIntelligenceDeblurringArchitectureDenoisingNoise reductionMetricsPopularityRecent effortsFuture directionsAccuracy
2020
Noise reduction with cross-tracer and cross-protocol deep transfer learning for low-dose PET
Liu H, Wu J, Lu W, Onofrey JA, Liu YH, Liu C. Noise reduction with cross-tracer and cross-protocol deep transfer learning for low-dose PET. Physics In Medicine And Biology 2020, 65: 185006. PMID: 32924973, DOI: 10.1088/1361-6560/abae08.Peer-Reviewed Original ResearchDeep LearningHumansImage EnhancementPositron-Emission TomographyRadiation DosageSignal-To-Noise Ratio
2019
An investigation of quantitative accuracy for deep learning based denoising in oncological PET
Lu W, Onofrey JA, Lu Y, Shi L, Ma T, Liu Y, Liu C. An investigation of quantitative accuracy for deep learning based denoising in oncological PET. Physics In Medicine And Biology 2019, 64: 165019. PMID: 31307019, DOI: 10.1088/1361-6560/ab3242.Peer-Reviewed Original Research
2016
Noise suppressed partial volume correction for cardiac SPECT/CT
Chan C, Liu H, Grobshtein Y, Stacy MR, Sinusas AJ, Liu C. Noise suppressed partial volume correction for cardiac SPECT/CT. Medical Physics 2016, 43: 5225-5239. PMID: 27587054, PMCID: PMC5001975, DOI: 10.1118/1.4961391.Peer-Reviewed Original Research