2004
Neighbor-Constrained Segmentation With Level Set Based 3-D Deformable Models
Yang J, Staib LH, Duncan JS. Neighbor-Constrained Segmentation With Level Set Based 3-D Deformable Models. IEEE Transactions On Medical Imaging 2004, 23: 940-948. PMID: 15338728, PMCID: PMC2838450, DOI: 10.1109/tmi.2004.830802.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBrainComputer SimulationElasticityHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalInformation Storage and RetrievalMagnetic Resonance ImagingModels, BiologicalModels, StatisticalNumerical Analysis, Computer-AssistedPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySignal Processing, Computer-AssistedConceptsThree-dimensional medical imagesImage gray level informationGray level informationPoint distribution modelMedical imagesNeighbor objectsTraining imagesMedical imageryMultiple objectsDeformable modelObject shapeSynthetic dataLevel informationSegmentationMap shapeEstimation frameworkPosition relationshipPrior informationLevel set functionObjectsJoint probability distributionSet functionNeighboring shapesInformationImagesSegmentation of 3D Deformable Objects with Level Set Based Prior Models
Yang J, Tagare HD, Staib LH, Duncan JS. Segmentation of 3D Deformable Objects with Level Set Based Prior Models. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2004, 1: 85-88. PMID: 20300448, PMCID: PMC2840654, DOI: 10.1109/isbi.2004.1398480.Peer-Reviewed Original ResearchMultiple objectsMedical imagesObject shapeExplicit point correspondencesShape prior constraintVariation of objectsTraining imagesMultidimensional dataTraining phaseDeformable modelDeformable objectsPoint correspondencesSegmentationPrior constraintsPrior informationLevel set functionPrior modelEstimation modelImagesObjectsLevel setsSet functionMaximum ARepresentationPoint distribution
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
1992
Boundary finding with parametrically deformable models
Staib L, Duncan J. Boundary finding with parametrically deformable models. IEEE Transactions On Pattern Analysis And Machine Intelligence 1992, 14: 1061-1075. DOI: 10.1109/34.166621.Peer-Reviewed Original ResearchBoundary findingDeformable modelElliptic Fourier decompositionProbabilistic deformable modelGlobal shape informationShape informationSynthetic imagesOptimization problemFlexible constraintsPrior informationImage qualityIrregularity of shapeObjective functionPosteriori objective functionInformationSegmentationParametric modelProbability distributionImagesObjectsModelRepresentationConstraints
1989
Left ventricular analysis from cardiac images using deformable models
Staib L, Duncan J. Left ventricular analysis from cardiac images using deformable models. 1989, 427-430. DOI: 10.1109/cic.1988.72651.Peer-Reviewed Original ResearchDeformable modelImage understanding systemElliptic Fourier decompositionProbabilistic deformable modelCardiac image sequencesIntelligent segmentationSegmentation problemImage dataImage sequencesUnderstanding systemCardiac imagesOptimization problemFlexible constraintsLeft ventricular analysisIrregularity of shapeNatural objectsSegmentationQuantitative evaluationGood matchParametric modelVentricular analysisImagesSystemObjectsModelParametrically deformable contour models
Staib L, Duncan J. Parametrically deformable contour models. 2015 IEEE Conference On Computer Vision And Pattern Recognition (CVPR) 1989, 98-103. DOI: 10.1109/cvpr.1989.37834.Peer-Reviewed Original ResearchElliptic Fourier decompositionProbabilistic deformable modelVariety of imagesDeformable contour modelSegmentation problemImage dataBoundary findingShape informationDeformable modelInitial experimentationContour modelOptimization problemFlexible constraintsIrregularity of shapeBetter resultsNatural objectsSegmentationGood matchParametric modelImagesObjectsExperimentationModelInformationConstraints