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
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
2006
Towards pointwise motion tracking in echocardiographic image sequences – Comparing the reliability of different features for speckle tracking
Yu W, Yan P, Sinusas AJ, Thiele K, Duncan JS. Towards pointwise motion tracking in echocardiographic image sequences – Comparing the reliability of different features for speckle tracking. Medical Image Analysis 2006, 10: 495-508. PMID: 16574465, DOI: 10.1016/j.media.2005.12.003.Peer-Reviewed Original ResearchConceptsMotion trackingBetter compensation resultsRadio frequency signalsLarge deformationDisplacement estimationTissue motionFrequency signalsSmall deformationsRF signalCompensation resultsFiltered featuresTracking featuresDeformationLinear convolution modelExperiment resultsTrackingEchocardiographic image sequencesPhantom examplesReliability measuresImage sequencesB-modeInverse problemSignalsReliabilityDifferent features
2003
Combinative multi-scale level set framework for echocardiographic image segmentation
Lin N, Yu W, Duncan JS. Combinative multi-scale level set framework for echocardiographic image segmentation. Medical Image Analysis 2003, 7: 529-537. PMID: 14561556, DOI: 10.1016/s1361-8415(03)00035-5.Peer-Reviewed Original ResearchConceptsLevel set frameworkShape knowledgeTedious human effortsSet frameworkEchocardiographic image sequencesLine training processEchocardiographic image segmentationUltrasound imagesImage segmentationAutomatic segmentationHuman effortImage sequencesBoundary detectionCoarse boundariesEdge featuresTraining processShape templatePoor featuresEndocardial boundarySegmentationContour evolutionRegion homogeneityImagesExperimental resultsCoarse scale