2012
A Dynamical Appearance Model Based on Multiscale Sparse Representation: Segmentation of the Left Ventricle from 4D Echocardiography
Huang X, Dione DP, Compas CB, Papademetris X, Lin BA, Sinusas AJ, Duncan JS. A Dynamical Appearance Model Based on Multiscale Sparse Representation: Segmentation of the Left Ventricle from 4D Echocardiography. Lecture Notes In Computer Science 2012, 15: 58-65. PMID: 23286114, PMCID: PMC3889160, DOI: 10.1007/978-3-642-33454-2_8.Peer-Reviewed Original ResearchConceptsStatistical modelAppearance modelSparse representationIntensity modelPriorsShape predictionRepresentation methodMultiscale sparse representationSpatio-temporal coherenceSparse representation methodLocal appearanceImage sequencesModelRepresentationAppearance informationCoherenceRobustnessSegmentation accuracy
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
2010
3D Radio Frequency Ultrasound Cardiac Segmentation Using a Linear Predictor
Pearlman PC, Tagare HD, Sinusas AJ, Duncan JS. 3D Radio Frequency Ultrasound Cardiac Segmentation Using a Linear Predictor. Lecture Notes In Computer Science 2010, 13: 502-509. PMID: 20879268, PMCID: PMC3889143, DOI: 10.1007/978-3-642-15705-9_61.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsComputer SimulationDogsEchocardiography, Three-DimensionalImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalLinear ModelsModels, CardiovascularMyocardial InfarctionPattern Recognition, AutomatedRadio WavesReproducibility of ResultsSensitivity and SpecificityConceptsLeft ventricular endocardial boundaryStandard level setSpatio-temporal coherenceCardiac segmentationBoundary detectionImage inhomogeneityEndocardial boundarySegmentationGeometric constraintsManual tracingRadio frequency ultrasoundLinear predictorLevel setsRF dataEchocardiographic imagesB-mode dataTrackingImagesDataConstraintsSetDetection
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-out
2008
Bidirectional Segmentation of Three-Dimensional Cardiac MR Images Using a Subject-Specific Dynamical Model
Zhu Y, Papademetris X, Sinusas AJ, Duncan JS. Bidirectional Segmentation of Three-Dimensional Cardiac MR Images Using a Subject-Specific Dynamical Model. Lecture Notes In Computer Science 2008, 11: 450-457. PMID: 18982636, PMCID: PMC2829658, DOI: 10.1007/978-3-540-85990-1_54.Peer-Reviewed Original ResearchConceptsSubject-specific dynamical modelGeneric dynamical modelDynamical modelSpecific dynamical modelLocal shape variationsDynamic prediction algorithmCardiac sequenceStatistical modelStatic modelModel-based segmentationCardiac dynamicsPeriodic natureMotionCardiac motionAlgorithmShape variationSegmentation errorsErrorModelOne-outPrediction algorithmPropagationCardiac MR imagesCertain framesSegmentation results
2007
Boundary element method-based regularization for recovering of LV deformation
Yan P, Sinusas A, Duncan JS. Boundary element method-based regularization for recovering of LV deformation. Medical Image Analysis 2007, 11: 540-554. PMID: 17584521, DOI: 10.1016/j.media.2007.04.007.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsComputer SimulationDogsElasticityFinite Element AnalysisHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingModels, CardiovascularReproducibility of ResultsSensitivity and SpecificityStress, MechanicalVentricular Dysfunction, LeftConceptsBoundary element methodImage sequencesElement methodDisplacement fieldDense displacement fieldNew regularization modelDeformationRegularization modelCardiac magnetic resonance image sequencesMagnetic resonance image sequencesEchocardiographic image sequencesLattice densityFeature informationComputation timePhysical plausibilityImage dataDisplacementMatching strategy
2005
A Boundary Element-Based Approach to Analysis of LV Deformation
Yan P, Lin N, Sinusas AJ, Duncan JS. A Boundary Element-Based Approach to Analysis of LV Deformation. Lecture Notes In Computer Science 2005, 8: 778-785. PMID: 16685917, DOI: 10.1007/11566465_96.Peer-Reviewed Original Research
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