2024
Deep Learning-based Dynamic PET Intra-frame Motion Correction and Integration with Inter-frame Motion Estimation
Guo X, Tsai Y, Liu Q, Guo L, Valadez G, Dvornek N, Liu C. Deep Learning-based Dynamic PET Intra-frame Motion Correction and Integration with Inter-frame Motion Estimation. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10657268.Peer-Reviewed Original ResearchIntra-frame motionMotion correctionGated imagesLearning-based registration approachesDeep learning-based worksInter-frame motion estimationConventional image registrationLearning-based worksImage registrationMotion estimation processMotion estimation frameworkInter-frame registrationRespiratory gatingImprove image sharpnessInter-frameInference timeMotion estimationReconstructed framesDynamic PET datasetsGeneralization abilityPET imagingConventional registrationDynamic PET imagesImprove image qualityComputational inefficiencyTAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction
Guo X, Shi L, Chen X, Liu Q, Zhou B, Xie H, Liu Y, Palyo R, Miller E, Sinusas A, Staib L, Spottiswoode B, Liu C, Dvornek N. TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction. Medical Image Analysis 2024, 96: 103190. PMID: 38820677, PMCID: PMC11180595, DOI: 10.1016/j.media.2024.103190.Peer-Reviewed Original ResearchGenerative adversarial networkAdversarial networkMotion estimation accuracyInter-frame motionIntensity-based image registration techniqueAll-to-oneSegmentation masksImage registration techniquesOriginal frameTemporal informationDiagnosis accuracyMyocardial blood flowEstimation accuracyFrame conversionPositron emission tomographyNovel methodImage qualityPET datasetsRegistration techniqueNetworkCardiac positron emission tomographyBlood flowDynamic cardiac positron emission tomographyMotion correctionCoronary artery disease
2023
TAI-GAN: Temporally and Anatomically Informed GAN for Early-to-Late Frame Conversion in Dynamic Cardiac PET Motion Correction
Guo X, Shi L, Chen X, Zhou B, Liu Q, Xie H, Liu Y, Palyo R, Miller E, Sinusas A, Spottiswoode B, Liu C, Dvornek N. TAI-GAN: Temporally and Anatomically Informed GAN for Early-to-Late Frame Conversion in Dynamic Cardiac PET Motion Correction. Lecture Notes In Computer Science 2023, 14288: 64-74. PMID: 38464964, PMCID: PMC10923183, DOI: 10.1007/978-3-031-44689-4_7.Peer-Reviewed Original ResearchMCP-Net: Introducing Patlak Loss Optimization to Whole-Body Dynamic PET Inter-Frame Motion Correction
Guo X, Zhou B, Chen X, Chen M, Liu C, Dvornek N. MCP-Net: Introducing Patlak Loss Optimization to Whole-Body Dynamic PET Inter-Frame Motion Correction. IEEE Transactions On Medical Imaging 2023, 42: 3512-3523. PMID: 37368811, PMCID: PMC10751388, DOI: 10.1109/tmi.2023.3290003.Peer-Reviewed Original ResearchMotion estimation blockDeep learning benchmarksGood generalization capabilityMotion correctionMotion correction frameworkMotion prediction errorGeneralization capabilityNetwork performanceNeural networkMotion correction techniqueLearning benchmarksRegistration problemLoss functionEstimation blockLoss optimizationPenalty componentDynamic frameFitting errorSpatial alignmentParametric imagesSpatial misalignmentDynamic positron emission tomographySubject motionPrediction errorCorrection frameworkFast-MC-PET: A Novel Deep Learning-Aided Motion Correction and Reconstruction Framework for Accelerated PET
Zhou B, Tsai Y, Zhang J, Guo X, Xie H, Chen X, Miao T, Lu Y, Duncan J, Liu C. Fast-MC-PET: A Novel Deep Learning-Aided Motion Correction and Reconstruction Framework for Accelerated PET. Lecture Notes In Computer Science 2023, 13939: 523-535. DOI: 10.1007/978-3-031-34048-2_40.Peer-Reviewed Original ResearchReconstruction frameworkMotion correctionMotion-compensated reconstructionHigh-quality imagesHigh-quality reconstruction imagesReconstruction moduleFrame reconstructionReconstruction outputMotion correction methodMotion modelingReconstructed imagesReconstruction methodImage qualityMotion typesImagesPatient motionExperimental resultsMotion-induced artifactsAcquisition dataReconstruction imagesLong acquisition timesFrameworkMultiple typesLow SNRPET acquisitionDirect respiratory motion correction of whole-body PET images using a deep learning framework incorporating spatial information
Miao T, Tsai Y, Zhou B, Menard D, Schleyer P, Hong I, Casey M, Liu C. Direct respiratory motion correction of whole-body PET images using a deep learning framework incorporating spatial information. Progress In Biomedical Optics And Imaging 2023, 12463: 124633x-124633x-9. DOI: 10.1117/12.2654472.Peer-Reviewed Original ResearchDeep learning frameworkRespiratory motion correctionMotion-corrected imagesLearning frameworkImage domainSpatial informationData-driven gating methodMotion correctionMotion detection techniqueGround truth imagesU-NetTruth imagesPET imagesData driving methodImage reconstructionWhole-body PET imagesMotion sensorsDetection techniquesExternal motion sensorsCross validationImagesConvenient mannerFrameworkRespiratory motionInformation
2022
Event-by-Event 3D Continuous Motion Correction Based on a Data-Driven Motion Estimation Algorithm for 82Rb Myocardial Perfusion Imaging
Tsai Y, Fontaine K, Mulnix T, Armstrong I, Hayden C, Spottiswoode B, Casey M, Liu C. Event-by-Event 3D Continuous Motion Correction Based on a Data-Driven Motion Estimation Algorithm for 82Rb Myocardial Perfusion Imaging. 2022, 00: 1-4. DOI: 10.1109/nss/mic44845.2022.10399100.Peer-Reviewed Original ResearchMotion correctionData-driven motion estimationPET/CT scannerSuperior-inferior motionMotion effectsSilicon photomultipliersNEMA phantomReconstruction frameworkPET acquisitionReconstructed image qualityCardiac PETMotion estimation algorithmPatient datasetsImage qualityMyocardial perfusion imagingCorrectionMotion monitoringTemporal resolutionSiPMMotionPhotomultiplierMotion estimationMotion vectorsPhantomCorrection algorithmMCP-Net: Inter-frame Motion Correction with Patlak Regularization for Whole-body Dynamic PET
Guo X, Zhou B, Chen X, Liu C, Dvornek N. MCP-Net: Inter-frame Motion Correction with Patlak Regularization for Whole-body Dynamic PET. Lecture Notes In Computer Science 2022, 13434: 163-172. PMID: 38464686, PMCID: PMC10923180, DOI: 10.1007/978-3-031-16440-8_16.Peer-Reviewed Original ResearchConvolutional long short-term memory (ConvLSTM) layersLong short-term memory layersMotion estimation moduleShort-term memory layersDeep learning benchmarksEnhanced network performanceImage registration problemMotion correction frameworkMotion correctionU-NetNetwork performanceLearning benchmarksSimilarity measurementEstimation moduleRegistration problemGradient lossMemory layerLoss functionDynamic frameDynamic positron emission tomographyFitting errorSpatial alignmentSpatial misalignmentPatient motionModulePET respiratory motion correction: quo vadis?
Lamare F, Bousse A, Thielemans K, Liu C, Merlin T, Fayad H, Visvikis D. PET respiratory motion correction: quo vadis? Physics In Medicine And Biology 2022, 67: 03tr02. PMID: 34915465, DOI: 10.1088/1361-6560/ac43fc.Peer-Reviewed Original ResearchConceptsRespiratory motion correctionPET respiratory motion correctionMotion correctionGeneric motion modelImage reconstruction processRespiratory motion informationMotion estimationMotion informationTerms of synchronizationImage spaceSynchronization stepsReconstruction processMotion modelOverall approachPET/magnetic resonance imagingDevice systemRespiratory motionImaging devicesMRI deviceDevicesSynchronizationNumber of stepsComprehensive coverageDatasetGreat interest
2021
Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning
Shi L, Lu Y, Dvornek N, Weyman CA, Miller EJ, Sinusas AJ, Liu C. Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning. IEEE Transactions On Medical Imaging 2021, 40: 3293-3304. PMID: 34018932, PMCID: PMC8670362, DOI: 10.1109/tmi.2021.3082578.Peer-Reviewed Original ResearchConceptsConvolutional neural networkRegistration-based methodMotion correctionDynamic frameTracer distribution changeDynamic image dataPatient motion correctionPatient scansDeep learningPatient motionMotion estimationImage dataLSTM networkNeural networkRealistic patient motionTemporal informationMotion correction methodMotion detectionCardiac PETClinical workflowRigid translational motionFlow estimationNetworkPatient datasetsSuperior performanceMDPET: A Unified Motion Correction and Denoising Adversarial Network for Low-Dose Gated PET
Zhou B, Tsai YJ, Chen X, Duncan JS, Liu C. MDPET: A Unified Motion Correction and Denoising Adversarial Network for Low-Dose Gated PET. IEEE Transactions On Medical Imaging 2021, 40: 3154-3164. PMID: 33909561, PMCID: PMC8588635, DOI: 10.1109/tmi.2021.3076191.Peer-Reviewed Original ResearchConceptsMotion estimationPyramid networkAdversarial networkAccurate motion estimationMotion correctionLow-noise reconstructionGated positron emission tomographyMotion correction methodMotion estimation networkGated PET dataEstimation networkRecurrent layersDenoising NetworkRespiratory motion blurringExperimental resultsLow-noise imagesMotion blurringNoise levelCorrection methodNetworkPET reconstructionPrevious methodsImage qualityImagesEstimation
2020
Simultaneous Denoising and Motion Estimation for Low-Dose Gated PET Using a Siamese Adversarial Network with Gate-to-Gate Consistency Learning
Zhou B, Tsai Y, Liu C. Simultaneous Denoising and Motion Estimation for Low-Dose Gated PET Using a Siamese Adversarial Network with Gate-to-Gate Consistency Learning. Lecture Notes In Computer Science 2020, 12267: 743-752. DOI: 10.1007/978-3-030-59728-3_72.Peer-Reviewed Original ResearchMotion estimationMotion estimation networkRobust motion estimationMotion correction methodRespiratory motion blurringEstimation networkNoise ratioMotion correctionMotion blurringImage volumesCorrection methodCorrection stepMotion vectorsGateSimultaneous denoisingImage qualityEstimationAdversarial network
2019
Deep Learning based Respiratory Pattern Classification and Applications in PET/CT Motion Correction
Guo Y, Dvornek N, Lu Y, Tsai Y, Hamill J, Casey M, Liu C. Deep Learning based Respiratory Pattern Classification and Applications in PET/CT Motion Correction. 2019, 00: 1-5. DOI: 10.1109/nss/mic42101.2019.9059783.Peer-Reviewed Original ResearchDeep learningNeural networkMotion correction methodDeep neural networksDeep learning modelsHybrid neural networkConvolutional layersHigh prediction accuracyRecurrent layersGeneralization capabilityData preprocessingLearning modelPattern classificationRespiratory motionAnzai systemLoss functionLinear classifierPrediction accuracyIntra-gate motionRPM systemMotion correctionTumor detectionNetworkIrregular breathersCT images
2018
Respiratory Motion Compensation for PET/CT with Motion Information Derived from Matched Attenuation-Corrected Gated PET Data
Lu Y, Fontaine K, Mulnix T, Onofrey JA, Ren S, Panin V, Jones J, Casey ME, Barnett R, Kench P, Fulton R, Carson RE, Liu C. Respiratory Motion Compensation for PET/CT with Motion Information Derived from Matched Attenuation-Corrected Gated PET Data. Journal Of Nuclear Medicine 2018, 59: 1480-1486. PMID: 29439015, PMCID: PMC6126443, DOI: 10.2967/jnumed.117.203000.Peer-Reviewed Original ResearchConceptsMotion correction frameworkMotion informationReference gatePET reconstructionMotion estimation accuracyGated PET dataMotion compensation approachMotion correctionMotion compensation methodMotion estimationRespiratory motion compensationAttenuation correction artifactsLung cancer datasetMotion compensationCT imagesNAC approachReconstruction algorithmPET dataPET imagesNew frameworkInaccurate localizationCancer datasetsBreathing variationsAttenuation correction mapsHuman datasets
2017
Investigation of Sub-Centimeter Lung Nodule Quantification for Low-Dose PET
Lu Y, Fontaine K, Germino M, Mulnix T, Casey M, Carson R, Liu C. Investigation of Sub-Centimeter Lung Nodule Quantification for Low-Dose PET. IEEE Transactions On Radiation And Plasma Medical Sciences 2017, 2: 41-50. DOI: 10.1109/trpms.2017.2778008.Peer-Reviewed Original ResearchMotion amplitudeLarge motion amplitudesVoxel sizeRespiratory motion correctionComprehensive simulationsReconstruction voxel sizeSimulationsMotion correctionPhantom studyFlight positron emission tomographyResolution recovery reconstructionMore accurate quantificationReconstruction algorithmAccurate quantificationHigh-resolution timeDifferent upsampling methodsUpsampling methodPositron emission tomographyAmplitudeSizeAdditional reductionNon-Rigid Event-by-Event Continuous Respiratory Motion Compensated List-Mode Reconstruction for PET
Chan C, Onofrey J, Jian Y, Germino M, Papademetris X, Carson RE, Liu C. Non-Rigid Event-by-Event Continuous Respiratory Motion Compensated List-Mode Reconstruction for PET. IEEE Transactions On Medical Imaging 2017, 37: 504-515. PMID: 29028189, PMCID: PMC7304524, DOI: 10.1109/tmi.2017.2761756.Peer-Reviewed Original ResearchConceptsMotion-compensated image reconstructionMotion fieldImage reconstructionReconstruction algorithmRespiratory motionNon-rigid motionNon-rigid motion correctionSignificant image blurringSystem matrixMotion correctionSystem matrix calculationMotionImage blurringSuperior image qualityTracer concentrationRigid motionReference locationMatrix calculationList-mode reconstruction algorithmMotion correlationDynamics studyImage quality
2013
Event‐by‐event respiratory motion correction for PET with 3D internal‐1D external motion correlation
Chan C, Jin X, Fung EK, Naganawa M, Mulnix T, Carson RE, Liu C. Event‐by‐event respiratory motion correction for PET with 3D internal‐1D external motion correlation. Medical Physics 2013, 40: 112507. PMID: 24320466, DOI: 10.1118/1.4826165.Peer-Reviewed Original ResearchMeSH KeywordsCarcinoma, Non-Small-Cell LungFluorine RadioisotopesHealthy VolunteersHumansHypoxiaImage Processing, Computer-AssistedImaging, Three-DimensionalInsulin-Secreting CellsKidneyLung NeoplasmsMisonidazoleMovementPancreasPositron-Emission TomographyRegression AnalysisReproducibility of ResultsRespirationSignal Processing, Computer-AssistedTetrabenazineX-Ray Microtomography
2011
Respiratory Gating for A Stationary Dedicated Cardiac SPECT System
Liu C, Chan C, Harris M, Le M, Biondi J, Volokh L, Sinusas A. Respiratory Gating for A Stationary Dedicated Cardiac SPECT System. 2011, 2898-2901. DOI: 10.1109/nssmic.2011.6152514.Peer-Reviewed Original ResearchCardiac SPECT systemDedicated cardiac SPECT systemsRespiratory motion correctionTemporal dataSlow gantry rotationData acquisitionCompressive sensorSPECT systemConventional SPECT systemImage qualityMotion correctionRespiratory gating techniquePhysical phantomRespiratory motionContrast recoveryRespiratory gatingUngated imagesImagesRespiratory triggersSystemGating techniqueMyocardial perfusion SPECTUpper abdomenLower chestRespiratory motion correction for quantitative PET/CT using all detected events with internal—external motion correlation
Liu C, Alessio AM, Kinahan PE. Respiratory motion correction for quantitative PET/CT using all detected events with internal—external motion correlation. Medical Physics 2011, 38: 2715-2723. PMID: 21776808, PMCID: PMC3107832, DOI: 10.1118/1.3582692.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtifactsHumansImage EnhancementImage Interpretation, Computer-AssistedMotionMovementNeoplasmsPositron-Emission TomographyReproducibility of ResultsRespiratory MechanicsRespiratory-Gated Imaging TechniquesSensitivity and SpecificityStatistics as TopicSubtraction TechniqueTomography, X-Ray ComputedConceptsPET listmode dataInternal motionsExternal motion signalExternal respiratory signalListmode dataTumor motion informationRespiratory-gated PET imagesCT attenuation mapsMotion correlationPhantom experimentsRespiratory motion signalMotion degradationMotion correctionTumor motionSUVmax increaseAttenuation mapResidual motionAttenuation correctionSinogramRespiratory motion correctionQuantitative PET/CTMotionReference frameRespiratory motionPET images