2002
Prior Shape Models for Boundary Finding
Staib L. Prior Shape Models for Boundary Finding. 2002, 30-33. DOI: 10.1109/isbi.2002.1029185.Peer-Reviewed Original ResearchBoundary findingTraining setAvailable training setPrior shape informationPrior informationPrior shape modelImage informationPrior shapeShape informationTarget objectBayesian formulationShape modelStatistical variationSmoothness constraintShape parametersNatural approachPosterior probabilityGeneric informationInformationObjectsAdditional flexibilitySetKey componentImagesSimilar shape
1998
Volumetric layer segmentation using coupled surfaces propagation
Zeng X, Staib L, Schultz R, Duncan J. Volumetric layer segmentation using coupled surfaces propagation. 2015 IEEE Conference On Computer Vision And Pattern Recognition (CVPR) 1998, 708-715. DOI: 10.1109/cvpr.1998.698681.Peer-Reviewed Original ResearchMedical image analysisUseful image informationMagnetic resonance brain imagesImage-derived informationImage gradient informationLevel set implementationGray level valuesEasy initializationSegmentation problemImage informationAutomatic segmentationGradient informationSet implementationBrain imagesLayer segmentationComputational efficiencyNon-brain structuresLeft ventricle myocardiumImage analysisSegmentationInformationNew approachTest examplesSurface propagationVentricle myocardium
1996
Parameterized Feasible Boundaries in Gradient Vector Fields
Worring M, Smeulders A, Staib L, Duncan J. Parameterized Feasible Boundaries in Gradient Vector Fields. Computer Vision And Image Understanding 1996, 63: 135-144. DOI: 10.1006/cviu.1996.0009.Peer-Reviewed Original ResearchImage informationModel-based segmentation procedureObject boundariesSegmentation of imagesDirectional gradient informationLocal image informationObjective functionReal medical imagesObject of interestObject boundary extractionMedical imagesImage dataSmoothness objectiveConflicting objectsBoundary extractionComplex imagesGradient informationArtificial dataSegmentation procedureFeasible boundaryGradient magnitudeSegmentationPhysical feasibilityImagesObjects
1993
Parameterized feasible boundaries in gradient vector fields
Worring M, Smeulders A, Staib L, Duncan J. Parameterized feasible boundaries in gradient vector fields. Lecture Notes In Computer Science 1993, 687: 48-61. DOI: 10.1007/bfb0013780.Peer-Reviewed Original ResearchObject boundariesMedical imagesModel-based segmentation procedureComplex medical imagesSegmentation of imagesDirectional gradient informationLocal image informationReal medical imagesObject of interestImage informationImage dataSmoothness objectiveConflicting objectsNew objective functionProblem of extractionGradient informationArtificial dataSegmentation procedureFeasible boundarySegmentationPhysical feasibilityImagesObjective functionObjectsGradient vector field