Featured Publications
Cross-Attention for Improved Motion Correction in Brain PET
Cai Z, Zeng T, Lieffrig E, Zhang J, Chen F, Toyonaga T, You C, Xin J, Zheng N, Lu Y, Duncan J, Onofrey J. Cross-Attention for Improved Motion Correction in Brain PET. Lecture Notes In Computer Science 2023, 14312: 34-45. PMID: 38174216, PMCID: PMC10758996, DOI: 10.1007/978-3-031-44858-4_4.Peer-Reviewed Original ResearchDeep learning networkCross-attention mechanismDeep learning benchmarksMotion correctionTraining data domainPET list-mode dataPET image reconstructionQuality of reconstructionData domainCross attentionLearning networkSupervised mannerLearning benchmarksReference imageMotion trackingInherent informationList-mode dataImage reconstructionBrain PET dataPrediction resultsDifferent scannersHead motionImproved motion correctionNetworkSpatial correspondence
2023
Spatial Normalization to Improve Deep Learning-based Head Motion Correction in PET
Zhang J, Lieffrig E, Zeng T, You C, Cai Z, Toyonaga T, Lu Y, Onofrey J. Spatial Normalization to Improve Deep Learning-based Head Motion Correction in PET. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338387.Peer-Reviewed Original ResearchTeacher’s PET: Semi-supervised Deep Learning for PET Head Motion Correction
Zeng T, You C, Cai Z, Lieffrig E, Zhang J, Chen F, Lu Y, Onofrey J. Teacher’s PET: Semi-supervised Deep Learning for PET Head Motion Correction. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10337834.Peer-Reviewed Original ResearchMotion tracking methodHead motion correctionMotion trackingExtra hardwareMotion estimatesTracking methodSemi-supervised deep learningSupervised deep learning methodsQuality training dataDeep learning methodsMean teacher modelSemi-supervised mannerMotion correctionMotion detectionHead motionCorrection networkDeep learningInaccurate quantitative resultsTraining dataLearning methodsBetter generalizationMotionLow resolutionCorrection resultsPerformanceImage Intensity Normalization Benefits Deep Learning Brain PET Motion Correction
Lieffrig E, Zhang J, Zeng T, Cai Z, You C, Lu Y, Onofrey J. Image Intensity Normalization Benefits Deep Learning Brain PET Motion Correction. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338194.Peer-Reviewed Original ResearchInput data normalizationImage intensity normalizationNeural network inputsMedical imaging researchPET motion correctionPre-processing stepMotion prediction errorMotion correctionIntensity normalizationNetwork inputsMotion predictionHead motion correctionInput dataTesting subjectsData normalizationEarly framesSuch methodsPrediction errorImaging researchDifferent normalization strategiesNormalization strategyMachineAlgorithmTaskValue analysisMulti-Task Deep Learning and Uncertainty Estimation for Pet Head Motion Correction
Lieffrig E, Zeng T, Zhang J, Fontaine K, Fang X, Revilla E, Lu Y, Onofrey J. Multi-Task Deep Learning and Uncertainty Estimation for Pet Head Motion Correction. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2023, 00: 1-5. PMID: 38111738, PMCID: PMC10725741, DOI: 10.1109/isbi53787.2023.10230791.Peer-Reviewed Original ResearchMulti-task deep learningMulti-task architectureMonte Carlo dropoutTesting subjectsDeep learningMotion tracking deviceSupervised learningMotion correction methodNetwork predictionHead motion correctionAppearance predictionReconstructed imagesPrediction performanceImage acquisitionImage qualityTracking deviceMotion correctionLearning processUncertainty estimationTomography image acquisitionHead motionPrediction uncertaintyLearningQualitative resultsArchitecture
2022
Multi-tracer Deep Learning for PET Head Motion Correction
Lieffrig E, Zeng T, Zhang J, Fang X, Revilla E, Lu Y, Onofrey J. Multi-tracer Deep Learning for PET Head Motion Correction. 2022, 00: 1-4. DOI: 10.1109/nss/mic44845.2022.10399143.Peer-Reviewed Original ResearchCamera motion trackingHead motionMotion correction performanceHead motion correctionRigid head motionContinuous head motionTransform blockFeature-wiseSupervised learningDeep learningMotion correctionBrain positron emission tomographyMotion trackingTracking hardwareExternal devicesCorrect performanceImage qualityQuantification errorsPositron emission tomographyQualitative resultsCorrection resultsLearningTracer typeMotionHardwareSupervised Deep Learning for Head Motion Correction in PET
Zeng T, Zhang J, Revilla E, Lieffrig E, Fang X, Lu Y, Onofrey J. Supervised Deep Learning for Head Motion Correction in PET. Lecture Notes In Computer Science 2022, 13434: 194-203. PMID: 38107622, PMCID: PMC10725740, DOI: 10.1007/978-3-031-16440-8_19.Peer-Reviewed Original ResearchDeep learning-based algorithmMotion tracking informationHead motion correctionNovel deep learningLearning-based algorithmMotion correctionDeep learningRegression layerEncoder layersTracking hardwareNetwork performanceSupervised mannerTracking informationAblation studiesRegistration approachCloud representationBrain positron emission tomography (PET) imagingTransformation layerDesign choicesReconstructed imagesPrediction performanceExternal devicesImage analysisTransformation parametersHead motion
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
Non-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