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 shapesInformationImages
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 distributionFrameworkNonlinear Estimation and Modeling of fMRI Data Using Spatio-temporal Support Vector Regression
Wang YM, Schultz RT, Constable RT, Staib LH. Nonlinear Estimation and Modeling of fMRI Data Using Spatio-temporal Support Vector Regression. Lecture Notes In Computer Science 2003, 18: 647-659. PMID: 15344495, DOI: 10.1007/978-3-540-45087-0_54.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceBrainBrain MappingCluster AnalysisComputer SimulationEvoked Potentials, VisualHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingModels, BiologicalModels, StatisticalNonlinear DynamicsPattern Recognition, AutomatedRegression AnalysisReproducibility of ResultsSensitivity and SpecificitySignal Processing, Computer-AssistedSubtraction TechniqueConceptsGeneral nonlinear frameworkStatistical learning methodologySupport vector regressionNonlinear estimationVector regressionNonlinear frameworkMultiresolution signal analysisLinear modelMotion estimationMulti-task studyMost current methodsData-driven methodSpatio-temporal autocorrelationEstimationVector machineEasy incorporationNoise componentsLearning methodologyNovel formulationSignal analysisData analysisInterpolation