2016
Is there an added value of a hepatobiliary phase with gadoxetate disodium following conventional MRI with an extracellular gadolinium agent in a single imaging session for detection of primary hepatic malignancies?
Pahade JK, Juice D, Staib L, Israel G, Cornfeld D, Mitchell K, Weinreb J. Is there an added value of a hepatobiliary phase with gadoxetate disodium following conventional MRI with an extracellular gadolinium agent in a single imaging session for detection of primary hepatic malignancies? Abdominal Radiology 2016, 41: 1270-1284. PMID: 26800701, DOI: 10.1007/s00261-016-0635-9.Peer-Reviewed Original Research
2015
Segmenting the Brain Surface from CT Images with Artifacts Using Dictionary Learning for Non-rigid MR-CT Registration
Onofrey JA, Staib LH, Papademetris X. Segmenting the Brain Surface from CT Images with Artifacts Using Dictionary Learning for Non-rigid MR-CT Registration. Lecture Notes In Computer Science 2015, 24: 662-674. PMID: 26221711, PMCID: PMC5266617, DOI: 10.1007/978-3-319-19992-4_52.Peer-Reviewed Original Research
2013
Contour tracking in echocardiographic sequences via sparse representation and dictionary learning
Huang X, Dione DP, Compas CB, Papademetris X, Lin BA, Bregasi A, Sinusas AJ, Staib LH, Duncan JS. Contour tracking in echocardiographic sequences via sparse representation and dictionary learning. Medical Image Analysis 2013, 18: 253-271. PMID: 24292554, PMCID: PMC3946038, DOI: 10.1016/j.media.2013.10.012.Peer-Reviewed Original ResearchConceptsContour trackerSparse representationEchocardiographic sequencesRegion-based level set segmentationLevel set segmentationLocal image appearanceManual tracingExpert manual tracingsMultiscale sparse representationImage sequencesSegmentation resultsAppearance modelSpatiotemporal priorsFirst frameMultilevel informationHuman data setsEjection fraction estimatesLocal appearanceImage appearanceDictionary learningShape modelContour trackingManual resultsData setsContour estimationLearning Nonrigid Deformations for Constrained Multi-modal Image Registration
Onofrey JA, Staib LH, Papademetris X. Learning Nonrigid Deformations for Constrained Multi-modal Image Registration. Lecture Notes In Computer Science 2013, 16: 171-178. PMID: 24505758, PMCID: PMC4044829, DOI: 10.1007/978-3-642-40760-4_22.Peer-Reviewed Original Research
2012
Simultaneous Nonrigid Registration, Segmentation, and Tumor Detection in MRI Guided Cervical Cancer Radiation Therapy
Lu C, Chelikani S, Jaffray DA, Milosevic MF, Staib LH, Duncan JS. Simultaneous Nonrigid Registration, Segmentation, and Tumor Detection in MRI Guided Cervical Cancer Radiation Therapy. IEEE Transactions On Medical Imaging 2012, 31: 1213-1227. PMID: 22328178, PMCID: PMC3889159, DOI: 10.1109/tmi.2012.2186976.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsFemaleHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingPattern Recognition, AutomatedRadiotherapy, ConformalRadiotherapy, Image-GuidedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueUterine Cervical Neoplasms
2011
Fasciculography: Robust Prior-Free Real-Time Normalized Volumetric Neural Tract Parcellation
Ho P, Wang F, Papademetris X, Blumberg HP, Staib LH. Fasciculography: Robust Prior-Free Real-Time Normalized Volumetric Neural Tract Parcellation. IEEE Transactions On Medical Imaging 2011, 31: 217-230. PMID: 21914568, PMCID: PMC3640528, DOI: 10.1109/tmi.2011.2167629.Peer-Reviewed Original ResearchConceptsDiffusion tensor magnetic resonance imagesLess human interventionSearch spaceAbnormality detectionHuman interventionDiffusion tensor fieldsAbove problemsOrientation informationNonrigid registrationIncomplete reconstructionStreamline trackingTrackingOrientation errorsMagnetic resonance imagesImage artifactsTracking errorFiber trackingWhite matter fiber tractsLocal noiseTensor fieldsResonance imagesParcellation methodSame timeInitializationViable tool
2009
Using Perturbation theory to reduce noise in diffusion tensor fields
Bansal R, Staib LH, Xu D, Laine AF, Liu J, Peterson BS. Using Perturbation theory to reduce noise in diffusion tensor fields. Medical Image Analysis 2009, 13: 580-597. PMID: 19540791, PMCID: PMC2782748, DOI: 10.1016/j.media.2009.05.001.Peer-Reviewed Original ResearchConceptsTensor fieldsDiffusion tensor fieldsPerturbation theoryMarkov random fieldPrior termDifferent spatial directionsRandom fieldsSymmetric tensorsRiemannian distanceSpatial directionsWhite matter fiber bundlesSmoothed fieldsLikelihood termEigenvaluesOriginal fieldEigenvectorsTensorReal-world datasetsDTI datasetsHomogeneous regionsTheoryLow signalNoiseNoise ratioFine structureVolumetric Shape Model for Oriented Tubular Structure from DTI Data
Ho HP, Papademetris X, Wang F, Blumberg HP, Staib LH. Volumetric Shape Model for Oriented Tubular Structure from DTI Data. Lecture Notes In Computer Science 2009, 12: 18-25. PMID: 20426091, PMCID: PMC2863144, DOI: 10.1007/978-3-642-04271-3_3.Peer-Reviewed Original ResearchConceptsBrain DTI dataMagnetic resonance diffusion tensor imagesContinuous modelStatistical methodsDiffusion tensor imagesSynthetic dataShape modelBoundary findingPoint correspondencesShape priorsDTI dataShape analysisVolumetric shapeTensor imagesWhole volumePriorsShape normalizationVolumetric shape modelsModelShapeOrientation information
2008
Calculation of the confidence intervals for transformation parameters in the registration of medical images
Bansal R, Staib LH, Laine AF, Xu D, Liu J, Posecion LF, Peterson BS. Calculation of the confidence intervals for transformation parameters in the registration of medical images. Medical Image Analysis 2008, 13: 215-233. PMID: 19138877, PMCID: PMC2891652, DOI: 10.1016/j.media.2008.09.002.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceConfidence IntervalsCorpus CallosumData Interpretation, StatisticalHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueConceptsSimilarity transformationMultivariate GaussianLeast squares estimationTransformation parametersMathematical frameworkRandom variablesPresence of noiseCovariance matrixLandmark pointsQuantifying errorsSimilarity parameterAmount of misregistrationInherent technological limitationsAmount of noiseGaussianCoordinatesInevitable errorsReal-world datasetsFunctional relationAmount of blurErrorParametersWorld datasetsNoiseConfidence intervalsUsing Perturbation Theory to Compute the Morphological Similarity of Diffusion Tensors
Bansal R, Staib L, Xu D, Laine A, Royal J, Peterson B. Using Perturbation Theory to Compute the Morphological Similarity of Diffusion Tensors. IEEE Transactions On Medical Imaging 2008, 27: 589-607. PMID: 18450533, PMCID: PMC2398733, DOI: 10.1109/tmi.2007.912391.Peer-Reviewed Original ResearchPhysical-Space Refraction-Corrected Transmission Ultrasound Computed Tomography Made Computationally Practical
Li S, Mueller K, Jackowski M, Dione D, Staib L. Physical-Space Refraction-Corrected Transmission Ultrasound Computed Tomography Made Computationally Practical. Lecture Notes In Computer Science 2008, 11: 280-288. PMID: 18982616, DOI: 10.1007/978-3-540-85990-1_34.Peer-Reviewed Original ResearchConceptsUltrasound Computed TomographyHigh-quality image reconstructionIterative reconstruction frameworkReconstruction frameworkReconstruction qualityComputational platformInteractive demandsTracking approachImage reconstructionConsiderable computational expenseComputational expenseCT frameworkImaged tissueFrameworkEikonal solverArchitectureTrackingPlatformProper modelingSolverComputationallyWave-front trackingCapabilityEikonal equationBayesian Analysis of fMRI Data with ICA Based Spatial Prior
Bathula DR, Tagare HD, Staib LH, Papademetris X, Schultz RT, Duncan JS. Bayesian Analysis of fMRI Data with ICA Based Spatial Prior. Lecture Notes In Computer Science 2008, 11: 246-254. PMID: 18982612, PMCID: PMC2864117, DOI: 10.1007/978-3-540-85990-1_30.Peer-Reviewed Original Research
2007
Statistical Analyses of Brain Surfaces Using Gaussian Random Fields on 2-D Manifolds
Bansal R, Staib LH, Xu D, Zhu H, Peterson BS. Statistical Analyses of Brain Surfaces Using Gaussian Random Fields on 2-D Manifolds. IEEE Transactions On Medical Imaging 2007, 26: 46-57. PMID: 17243583, PMCID: PMC2366175, DOI: 10.1109/tmi.2006.884187.Peer-Reviewed Original Research
2006
Advances in Radiologic Image Analysis from MICCAI 2005
Staib LH, Styner M. Advances in Radiologic Image Analysis from MICCAI 2005. Academic Radiology 2006, 13: 1053-1054. PMID: 16935716, DOI: 10.1016/j.acra.2006.06.013.Peer-Reviewed Original Research
2005
White matter tractography by anisotropic wavefront evolution and diffusion tensor imaging
Jackowski M, Kao CY, Qiu M, Constable RT, Staib LH. White matter tractography by anisotropic wavefront evolution and diffusion tensor imaging. Medical Image Analysis 2005, 9: 427-440. PMID: 16040268, PMCID: PMC2839167, DOI: 10.1016/j.media.2005.05.008.Peer-Reviewed Original Research
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
Image Processing and Analysis at IPAG
Duncan JS, Staib LH. Image Processing and Analysis at IPAG. IEEE Transactions On Medical Imaging 2003, 22: 1505. PMID: 14649742, DOI: 10.1109/tmi.2003.819935.Peer-Reviewed Original ResearchNeighbor-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