2023
Multi-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 typeMotionHardware
2021
Weakly Supervised Deep Learning for Aortic Valve Finite Element Mesh Generation from 3D CT Images
Pak D, Liu M, Ahn S, Caballero A, Onofrey J, Liang L, Sun W, Duncan J. Weakly Supervised Deep Learning for Aortic Valve Finite Element Mesh Generation from 3D CT Images. Lecture Notes In Computer Science 2021, 12729: 637-648. DOI: 10.1007/978-3-030-78191-0_49.Peer-Reviewed Original ResearchSupervised deep learningTranscather aortic valve replacementDeep learningSegmentation labelsMesh generationCorrespondence accuracyHeavy assumptionsFinite element mesh generationMesh topologyVolumetric meshLow contrastSignificant bottleneckValve modelingProblem formulationPrediction modelModel performanceCT imagesDeformation strategyLarge amountImagesBottleneckLearningMeshFrameworkLabels
2020
Sparse Data–Driven Learning for Effective and Efficient Biomedical Image Segmentation
Onofrey JA, Staib LH, Huang X, Zhang F, Papademetris X, Metaxas D, Rueckert D, Duncan JS. Sparse Data–Driven Learning for Effective and Efficient Biomedical Image Segmentation. Annual Review Of Biomedical Engineering 2020, 22: 1-27. PMID: 32169002, PMCID: PMC9351438, DOI: 10.1146/annurev-bioeng-060418-052147.Peer-Reviewed Original ResearchSupervised Machine Learning in Oncology: A Clinician's Guide
Murali N, Kucukkaya A, Petukhova A, Onofrey J, Chapiro J. Supervised Machine Learning in Oncology: A Clinician's Guide. Digestive Disease Interventions 2020, 04: 073-081. PMID: 32869010, PMCID: PMC7456427, DOI: 10.1055/s-0040-1705097.Peer-Reviewed Original ResearchMachine learningSupervised machineSupervised machine learning methodsNew data processing technologiesLarge volume dataData processing technologySupervised machine learningMachine learning methodsSelf-improving modelElectronic health recordsLearning methodsHealth recordsComputer algorithmWidespread adoptionLearningMeaningful insightsMachineAlgorithmTechnologyTechniqueFrameworkInformationAdoptionDataApplications