2020
A Semi-supervised Joint Network for Simultaneous Left Ventricular Motion Tracking and Segmentation in 4D Echocardiography
Ta K, Ahn SS, Stendahl JC, Sinusas AJ, Duncan JS. A Semi-supervised Joint Network for Simultaneous Left Ventricular Motion Tracking and Segmentation in 4D Echocardiography. Lecture Notes In Computer Science 2020, 12266: 468-477. PMID: 33094292, PMCID: PMC7576886, DOI: 10.1007/978-3-030-59725-2_45.Peer-Reviewed Original Research
2009
A 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. Lecture Notes In Computer Science 2009, 5761: 206-213. PMID: 20054422, PMCID: PMC2801876, DOI: 10.1007/978-3-642-04268-3_26.Peer-Reviewed Original ResearchSubject-specific dynamical modelCurrent frameMotion patternsRecursive Bayesian frameworkSegmentation taskPast framesAutomatic segmentationPrevious frameSegmentation processShape priorsLV segmentationManual segmentationSegmentationIntensity informationCardiac sequenceEchocardiographic sequencesStatic modelPrior knowledgeTemporal coherenceDynamical shape priorsCardiac motionCardiac modelsBayesian frameworkGeneric dynamical modelEchocardiographic imagesA 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
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
1996
Tracking myocardial deformation using phase contrast MR velocity fields: a stochastic approach
Meyer FG, Constable RT, Sinusas AJ, Duncan JS. Tracking myocardial deformation using phase contrast MR velocity fields: a stochastic approach. IEEE Transactions On Medical Imaging 1996, 15: 453-465. PMID: 18215927, DOI: 10.1109/42.511749.Peer-Reviewed Original ResearchVelocity fieldVelocity dataKalman filterAverage errorField velocityVelocity vectorMR velocity dataDeformationEntire cardiac cycleNew approachBasic dynamical modelImage framesMotion problemCardiac motionLV motionFilterMotionContour dataStochastic approachThree-dimensional datasetsDynamical modelNoisePath lengthKinematicsPhantom data