2019
Flow network tracking for spatiotemporal and periodic point matching: Applied to cardiac motion analysis
Parajuli N, Lu A, Ta K, Stendahl J, Boutagy N, Alkhalil I, Eberle M, Jeng GS, Zontak M, O'Donnell M, Sinusas AJ, Duncan JS. Flow network tracking for spatiotemporal and periodic point matching: Applied to cardiac motion analysis. Medical Image Analysis 2019, 55: 116-135. PMID: 31055125, PMCID: PMC6939679, DOI: 10.1016/j.media.2019.04.007.Peer-Reviewed Original ResearchConceptsDeformation/strainExcellent tracking accuracyEntire cardiac cycleTracking accuracyCardiac motion analysisAccurate estimationSurface pointsEchocardiographic image sequencesLV motionDisplacementMotion analysisImage sequencesCardiac cyclePoint matchingMotionConsecutive framesEstimationNetwork trackingImportant characteristicsSignificant promiseSchemeGood correlationFlow
2011
SEGMENTATION OF 3D RF ECHOCARDIOGRAPHY USING A JOINT SPATIO-TEMPORAL PREDICTOR AND SIGNAL INTENSITY MODEL
Pearlman P, Tagare H, Lin B, Sinusas A, Duncan J. SEGMENTATION OF 3D RF ECHOCARDIOGRAPHY USING A JOINT SPATIO-TEMPORAL PREDICTOR AND SIGNAL INTENSITY MODEL. 2011, 649-652. DOI: 10.1109/isbi.2011.5872490.Peer-Reviewed Original ResearchSpatio-temporal predictorsLeft ventricular segmentationSpatio-temporal coherenceSegmentation problemImage sequencesSubsequent framesVentricular segmentationSegmentationUltrasound sequencesVoxel intensitiesManual tracingLinear predictorLevel setsSpatial modelConditional modelInhomogeneity issuesFrameIntensity modelModelSet
2006
Sampled-Data ηα Filtering for Robust Kinematics Estimation: Applications to Biomechanics-Based Cardiac Image Analysis
Tong S, Sinusas A, Shi P. Sampled-Data ηα Filtering for Robust Kinematics Estimation: Applications to Biomechanics-Based Cardiac Image Analysis. 2014 IEEE International Conference On Image Processing (ICIP) 2006, 2525-2528. DOI: 10.1109/icip.2006.312955.Peer-Reviewed Original ResearchCanine MR phase contrast imagesPeriodic medical image sequencesContinuous-time state equationsDiscrete time instantsMore accurate estimation resultsAccurate estimation resultsCardiac image analysisKinematics estimationReal-world problemsMedical image sequencesState equationContinuous dynamicsParameter uncertaintiesSynthetic data experimentsModel uncertaintyState estimatesCardiac motion estimationTime instantsFiltering frameworkMotion estimationData disturbancesImage sequencesDiscrete measurementsNoisy natureData experimentsContinuous-Discrete Filtering for Cardiac Kinematics Estimation under Spatio-Temporal Biomechanical Constrains
Tong S, Sinusas A, Shi P. Continuous-Discrete Filtering for Cardiac Kinematics Estimation under Spatio-Temporal Biomechanical Constrains. 2006, 1: 167-170. DOI: 10.1109/icpr.2006.413.Peer-Reviewed Original ResearchCanine MR phase contrast imagesPeriodic medical image sequencesKinematics estimationMore accurate estimation resultsAccurate estimation resultsContinuous-time state equationsParameter uncertaintiesFiltering frameworkDiscrete time instantsState estimatesDiscrete filteringMedical image sequencesState equationDiscrete measurementsContinuous dynamicsTime instantsSynthetic data experimentsFiltering strategyImage sequencesData experimentsEstimation resultsNoisy natureEstimationMeasurementsCardiac dynamicsBoundary Element Method-Based Scattered Feature Interpolation Algorithm in the Analysis of LV Deformation
Yan P, Sinusas A, Duncan J. Boundary Element Method-Based Scattered Feature Interpolation Algorithm in the Analysis of LV Deformation. 2006, 1-8. DOI: 10.1109/cvprw.2006.47.Peer-Reviewed Original ResearchBoundary element methodElement methodFree-form deformationInterpolation algorithmDisplacement fieldImage sequencesDense displacement fieldLattice densityDeformationCardiac magnetic resonance image sequencesAccurate estimationForm deformationComputational efficiencyMagnetic resonance image sequencesStandard B-splinesRobust Point MatchingInterpolation methodPoint matchingComputation timeNew interpolation algorithmPhysical plausibilityB-splinesDensitySpatial positionImage-derived features
2004
Simultaneous Recovery of Left Ventricular Shape and Motion Using Meshfree Particle Framework
Wong A, Liu H, Sinusas A, Shi P. Simultaneous Recovery of Left Ventricular Shape and Motion Using Meshfree Particle Framework. 2004, 2: 1263-1266. DOI: 10.1109/isbi.2004.1398775.Peer-Reviewed Original ResearchMedical image analysisImage analysis frameworkCyclic motion modelPrior spatial distributionsComputation platformImage sequencesMeshfree particle methodMotion modelEpicardial boundariesTemporal coherenceImage analysisAnalysis frameworkDeformation resultsApplication resultsParticle methodComplex geometriesGood flexibilityVelocity informationExternal driving forceParticle frameworkGalerkin formulationSimultaneous recoveryMyocardial behaviorSalient featuresFramework
2001
Estimation of 3D left ventricular deformation from echocardiography
Papademetris X, Sinusas A, Dione D, Duncan J. Estimation of 3D left ventricular deformation from echocardiography. Medical Image Analysis 2001, 5: 17-28. PMID: 11231174, DOI: 10.1016/s1361-8415(00)00022-0.Peer-Reviewed Original ResearchConceptsDense motion fieldIsotropic linear elastic modelRegional cardiac deformationLinear elastic modelMotion fieldTerms of strainCardiac deformationFiber directionElastic modelDeformationHeart wallGood agreementHeart deformationImage sequencesWallEstimationSpecific directionUltrasound imagesQuantitative estimationInitial correspondenceField
2000
Estimating 3D Strain from 4D Cine-MRI and Echocardiography: In-Vivo Validation
Papademetris X, Sinusas A, Dione D, Constable R, Duncan J. Estimating 3D Strain from 4D Cine-MRI and Echocardiography: In-Vivo Validation. Lecture Notes In Computer Science 2000, 1935: 678-686. DOI: 10.1007/978-3-540-40899-4_70.Peer-Reviewed Original Research
1999
Volumetric Deformation Analysis Using Mechanics-Based Data Fusion: Applications in Cardiac Motion Recovery
Shi P, Sinusas A, Constable R, Duncan J. Volumetric Deformation Analysis Using Mechanics-Based Data Fusion: Applications in Cardiac Motion Recovery. International Journal Of Computer Vision 1999, 35: 87-107. DOI: 10.1023/a:1008163112590.Peer-Reviewed Original ResearchMotion estimationNon-rigid motion estimationInstantaneous velocity dataCardiac motion recoveryContinuum mechanics principlesMotion recovery problemData fusionImage sequencesVolumetric deformationPhysical objectsMechanics principlesDisplacement informationComplementary data sourcesDynamic behaviorMotion recoveryData sourcesVelocity dataRecovery problemMotion analysisNew methodDeformationEstimationMeaningful constraintsObjectsPatient diagnosisRecovery of Soft Tissue Object Deformation from 3D Image Sequences Using Biomechanical Models
Papademetris X, Shi P, Dione D, Sinusas A, Constable R, Duncan J. Recovery of Soft Tissue Object Deformation from 3D Image Sequences Using Biomechanical Models. Lecture Notes In Computer Science 1999, 1613: 352-357. DOI: 10.1007/3-540-48714-x_28.Peer-Reviewed Original Research3D Cardiac Deformation from Ultrasound Images
Papademetris X, Sinusas A, Dione D, Duncan J. 3D Cardiac Deformation from Ultrasound Images. Lecture Notes In Computer Science 1999, 1679: 420-429. DOI: 10.1007/10704282_46.Peer-Reviewed Original ResearchDense motion fieldRegional cardiac deformationCardiac deformationLinear elastic modelMotion fieldTerms of strainFiber directionElastic modelDeformationHeart wallUltrasound imagesGood agreementHeart deformationImage sequencesWallSpecific directionQuantitative estimationInitial correspondenceFieldFlow
1994
Shape-based 4D left ventricular myocardial function analysis
Shi P, Amini A, Robinson G, Sinusas A, Constable C, Duncan J. Shape-based 4D left ventricular myocardial function analysis. 1994, 88-97. DOI: 10.1109/bia.1994.315862.Peer-Reviewed Original ResearchFour-dimensional image dataImage analysis algorithmsSurface curvature estimationInitial experimental resultsImage dataImage sequencesImage analysis methodMotion trackingVisualization techniquesAnalysis algorithmImage-derived measuresDifferent modalitiesSurface triangulationExperimental resultsTemporal framesCurvature estimationLV motionRegional myocardial viabilityAlgorithmAnalysis methodTrackingNew developmentsTechniqueQuantitative measures