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
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