2022
CineCT platform for in vivo and ex vivo measurement of 3D high resolution Lagrangian strains in the left ventricle following myocardial infarction and intramyocardial delivery of theranostic hydrogel
Midgett D, Thorn S, Ahn S, Uman S, Avendano R, Melvinsdottir I, Lysyy T, Kim J, Duncan J, Humphrey J, Papademetris X, Burdick J, Sinusas A. CineCT platform for in vivo and ex vivo measurement of 3D high resolution Lagrangian strains in the left ventricle following myocardial infarction and intramyocardial delivery of theranostic hydrogel. Journal Of Molecular And Cellular Cardiology 2022, 166: 74-90. PMID: 35227737, PMCID: PMC9035115, DOI: 10.1016/j.yjmcc.2022.02.004.Peer-Reviewed Original Research
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 Research
2013
Contour tracking in echocardiographic sequences via sparse representation and dictionary learning
Huang X, Dione DP, Compas CB, Papademetris X, Lin BA, Bregasi A, Sinusas AJ, Staib LH, Duncan JS. Contour tracking in echocardiographic sequences via sparse representation and dictionary learning. Medical Image Analysis 2013, 18: 253-271. PMID: 24292554, PMCID: PMC3946038, DOI: 10.1016/j.media.2013.10.012.Peer-Reviewed Original ResearchConceptsContour trackerSparse representationEchocardiographic sequencesRegion-based level set segmentationLevel set segmentationLocal image appearanceManual tracingExpert manual tracingsMultiscale sparse representationImage sequencesSegmentation resultsAppearance modelSpatiotemporal priorsFirst frameMultilevel informationHuman data setsEjection fraction estimatesLocal appearanceImage appearanceDictionary learningShape modelContour trackingManual resultsData setsContour estimation
2012
Assessment of left ventricular 2D flow pathlines during early diastole using spatial modulation of magnetization with polarity alternating velocity encoding: A study in normal volunteers and canine animals with myocardial infarction
Zhang Z, Friedman D, Dione DP, Lin BA, Duncan JS, Sinusas AJ, Sampath S. Assessment of left ventricular 2D flow pathlines during early diastole using spatial modulation of magnetization with polarity alternating velocity encoding: A study in normal volunteers and canine animals with myocardial infarction. Magnetic Resonance In Medicine 2012, 70: 766-775. PMID: 23044637, PMCID: PMC3844046, DOI: 10.1002/mrm.24517.Peer-Reviewed Original ResearchMeSH KeywordsAdultAnimalsDiastoleDogsFemaleHealthy VolunteersHeart VentriclesHumansMaleMyocardial InfarctionVentricular Function, Left
2011
Segmentation of 3D radio frequency echocardiography using a spatio-temporal predictor
Pearlman PC, Tagare HD, Lin BA, Sinusas AJ, Duncan JS. Segmentation of 3D radio frequency echocardiography using a spatio-temporal predictor. Medical Image Analysis 2011, 16: 351-360. PMID: 22078842, PMCID: PMC3267850, DOI: 10.1016/j.media.2011.09.002.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsComputer SimulationDogsEchocardiography, Three-DimensionalHeart VentriclesImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalModels, CardiovascularModels, StatisticalPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueConceptsLeft ventricular endocardial boundarySpatio-temporal predictorsStandard level setRF dataSpatio-temporal coherenceNeighboring framesImage sequencesBoundary detectionMultiple framesImage inhomogeneitySegmentationEndocardial boundaryGeometric constraintsManual tracingRF ultrasoundAlgorithmLevel setsEchocardiographic imagesFrameConditional modelLinear predictorTrackingSpatial modelImagesRobustness
2009
Segmentation of the Left Ventricle from Cardiac MR Images Using a Subject-Specific Dynamical Model
Zhu Y, Papademetris X, Sinusas AJ, Duncan JS. Segmentation of the Left Ventricle from Cardiac MR Images Using a Subject-Specific Dynamical Model. IEEE Transactions On Medical Imaging 2009, 29: 669-687. PMID: 19789107, PMCID: PMC2832728, DOI: 10.1109/tmi.2009.2031063.Peer-Reviewed Original ResearchConceptsSubject-specific dynamical modelGeneric dynamical modelDynamical modelStatistical modelSpecific dynamical modelRecursive Bayesian frameworkDynamic prediction algorithmStatic modelBayesian frameworkCardiac sequenceMotion modelActive Appearance Motion ModelsError propagationSpecific motion patternsPeriodic natureExperimental resultsPropagationCardiac shapeSegmentation resultsBackward directionSequential segmentationDynamicsModelMotion patternsOne-outA dynamical shape prior for LV segmentation from RT3D echocardiography.
Zhu Y, Papademetris X, Sinusas AJ, Duncan JS. A dynamical shape prior for LV segmentation from RT3D echocardiography. 2009, 12: 206-13. PMID: 20425989, PMCID: PMC7814293.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceComputer SimulationComputer SystemsEchocardiography, Three-DimensionalHeart VentriclesHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalModels, AnatomicPattern Recognition, AutomatedPhantoms, ImagingReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueConceptsSubject-specific dynamical modelCurrent frameMotion patternsRecursive Bayesian frameworkSegmentation taskPast framesAutomatic segmentationPrevious frameSegmentation processLV segmentationManual segmentationSegmentationIntensity informationCardiac sequenceEchocardiographic sequencesStatic modelPrior knowledgeTemporal coherenceCardiac motionCardiac modelsBayesian frameworkGeneric dynamical modelEchocardiographic imagesFrameInter-subject variability
2007
Segmentation of Myocardial Volumes from Real-Time 3D Echocardiography Using an Incompressibility Constraint
Zhu Y, Papademetris X, Sinusas A, Duncan JS. Segmentation of Myocardial Volumes from Real-Time 3D Echocardiography Using an Incompressibility Constraint. Lecture Notes In Computer Science 2007, 10: 44-51. PMID: 18051042, DOI: 10.1007/978-3-540-75757-3_6.Peer-Reviewed Original ResearchConceptsAutomatic segmentationImage-derived informationLV endocardial boundariesFinal representationManual segmentationSegmentationEndocardial boundaryEpicardial boundariesReal-time 3D echocardiographyTight couplingNew approachThree-dimensional shapeConstraintsVariety of effortsRepresentationInformationNew imaging modalitySetLV Segmentation Through the Analysis of Radio Frequency Ultrasonic Images
Yan P, Jia CX, Sinusas A, Thiele K, O’Donnell M, Duncan JS. LV Segmentation Through the Analysis of Radio Frequency Ultrasonic Images. Lecture Notes In Computer Science 2007, 20: 233-244. PMID: 17633703, DOI: 10.1007/978-3-540-73273-0_20.Peer-Reviewed Original Research
2003
Neighbor-Constrained Segmentation with 3D Deformable Models
Yang J, Staib LH, Duncan JS. Neighbor-Constrained Segmentation with 3D Deformable Models. Lecture Notes In Computer Science 2003, 18: 198-209. PMID: 15344458, DOI: 10.1007/978-3-540-45087-0_17.Peer-Reviewed Original ResearchConceptsImage gray level informationGray level informationNeighbor objectsMedical imagesTraining imagesMedical imageryMultiple objectsDeformable modelSynthetic dataLevel informationSegmentationMap shapeEstimation frameworkPrior informationLevel set functionObjectsJoint probability distributionSet functionInformationImagesNovel methodMaximum AJoint density functionProbability distributionFramework
2002
Estimation of 3-D Left Ventricular Deformation from Medical Images Using Biomechanical Models
Papademetris* X, Sinusas AJ, Dione DP, Constable RT, Duncan JS. Estimation of 3-D Left Ventricular Deformation from Medical Images Using Biomechanical Models. IEEE Transactions On Medical Imaging 2002, 21: 786. PMID: 12374316, DOI: 10.1109/tmi.2002.801163.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsCoronary DiseaseDogsElasticityFinite Element AnalysisHeart VentriclesHumansImage EnhancementImaging, Three-DimensionalMagnetic Resonance Imaging, CineModels, CardiovascularPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificityStress, MechanicalConceptsDense motion fieldRegional cardiac deformationLinear elastic modelSoft tissue deformationMotion fieldTerms of strainBiomechanical modelDeformation estimationTissue deformationFiber directionDeformationThree-dimensional image sequencesCardiac deformationHeart wallGood agreementHeart deformationGeneric methodologyMuscle fiber directionImage-derived informationImage sequencesEstimationWallSpecific directionQuantitative estimationInitial correspondence
2001
A new method for quantification of spatial and temporal parameters of endocardial motion: evaluation of experimental infarction using magnetic resonance imaging.
Heller EN, Staib LH, Dione DP, Constable RT, Shi CQ, Duncan JS, Sinusas AJ. A new method for quantification of spatial and temporal parameters of endocardial motion: evaluation of experimental infarction using magnetic resonance imaging. Canadian Journal Of Cardiology 2001, 17: 309-18. PMID: 11264564.Peer-Reviewed Original Research