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
2000
Physical model-based non-rigid registration incorporating statistical shape information
Wang Y, Staib L. Physical model-based non-rigid registration incorporating statistical shape information. Medical Image Analysis 2000, 4: 7-20. PMID: 10972317, DOI: 10.1016/s1361-8415(00)00004-9.Peer-Reviewed Original ResearchConceptsStatistical shape informationStatistical shape modelDeformable elastic solidsComplex anatomical detailsIntensity similarity measureShape modelBayesian formulationBoundary shape informationViscous fluidCorresponding boundary pointsElastic solidsBoundary pointsDense setPhysical modelRobust approachSparse setReal medical imagesNumber of experimentsFirst methodShape informationSimilarity measureSetPhysical propertiesModelSmoothness
1998
Elastic model based non-rigid registration incorporating statistical shape information
Wang Y, Staib L. Elastic model based non-rigid registration incorporating statistical shape information. Lecture Notes In Computer Science 1998, 1496: 1162-1173. DOI: 10.1007/bfb0056306.Peer-Reviewed Original ResearchStatistical shape informationStatistical shape modelComplex anatomical detailsIntensity similarity measureShape modelElastic modelBayesian formulationBoundary shape informationCorresponding boundary pointsBoundary pointsDense setPhysical modelSparse setReal medical imagesNumber of experimentsShape informationRobust non-rigid registrationNew methodSimilarity measureModelSet
1997
An Integrated Approach for Locating Neuroanatomical Structure from MRI
Staib L, Chakraborty A, Duncan J. An Integrated Approach for Locating Neuroanatomical Structure from MRI. International Journal Of Pattern Recognition And Artificial Intelligence 1997, 11: 1247-1269. DOI: 10.1142/s0218001497000585.Peer-Reviewed Original ResearchHomogeneous region-classified areaPrior shape informationMR brain imagesMagnetic resonance imagesComputational overheadRegion informationShape informationBrain imagesSuch imagesExtra informationImproper initializationThree-dimensional imagesDeformable surfacesImagesExperimental resultsGauss divergence theoremWide availabilityInformationOverheadResonance imagesSegmentationIntegrated approachHigh-resolution magnetic resonance imagesAlgorithmInitialization
1996
Deformable boundary finding in medical images by integrating gradient and region information
Chakraborty A, Staib L, Duncan J. Deformable boundary finding in medical images by integrating gradient and region information. IEEE Transactions On Medical Imaging 1996, 15: 859-870. PMID: 18215965, DOI: 10.1109/42.544503.Peer-Reviewed Original ResearchBoundary findingMedical imagesHomogeneous region-classified areaBiomedical image analysisGray level homogeneityRegion-based segmentationReal medical imagesComputational overheadImage segmentationRegion informationShape informationPoor initializationPerceptual notionsImage analysisNumber of experimentsSegmentationVariety of limitationsGreen's theoremImagesUnified approachAuthors' approachKey issuesNew approachOverheadInformation
1994
Deformable boundary finding influenced by region homogeneity
Chakraborty A, Staib L, Duncan J. Deformable boundary finding influenced by region homogeneity. 2015 IEEE Conference On Computer Vision And Pattern Recognition (CVPR) 1994, 624-627. DOI: 10.1109/cvpr.1994.323790.Peer-Reviewed Original ResearchHomogeneous region-classified areaGray level homogeneityBoundary findingBiomedical image analysisRegion-based segmentationImage segmentationShape informationGreen's theoremPoor initializationConventional methodsPerceptual notionsRegion homogeneityImage analysisVariety of limitationsSegmentationUnified approachKey issuesAn integrated approach to boundary finding in medical images
Chakraborty A, Staib L, Duncan J. An integrated approach to boundary finding in medical images. 1994, 13-22. DOI: 10.1109/bia.1994.315870.Peer-Reviewed Original ResearchBoundary findingMedical imagesHomogeneous region-classified areaBiomedical image analysisGray level homogeneityReal medical imagesImage segmentationShape informationPoor initializationPerceptual notionsImage analysisNumber of experimentsSegmentationVariety of limitationsConventional gradientImagesUnified approachAuthors' approachKey issuesNew approachGreen's theoremConventional methodsIntegrated approachInitializationFinder
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
Parametrically 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