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