2023
Learning Sequential Information in Task-Based fMRI for Synthetic Data Augmentation
Wang J, Dvornek N, Staib L, Duncan J. Learning Sequential Information in Task-Based fMRI for Synthetic Data Augmentation. Lecture Notes In Computer Science 2023, 14312: 79-88. PMID: 39281201, PMCID: PMC11395879, DOI: 10.1007/978-3-031-44858-4_8.Peer-Reviewed Original ResearchFunctional magnetic resonance imagesData augmentationClassification taskSpecific cognitive tasksMedical image analysisSynthetic data augmentationEffective data augmentationDownstream learning tasksCognitive tasksVariational autoencoder modelLearning taskTraining dataAutoencoder modelTemporal informationTraining datasetSequential informationSynthetic imagesTaskFMRI sequencesImage analysisMultiple perspectivesMagnetic resonance imagesImagesDifferent alternativesPersistent issuePredicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learning
Kucukkaya A, Zeevi T, Chai N, Raju R, Haider S, Elbanan M, Petukhova-Greenstein A, Lin M, Onofrey J, Nowak M, Cooper K, Thomas E, Santana J, Gebauer B, Mulligan D, Staib L, Batra R, Chapiro J. Predicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learning. Scientific Reports 2023, 13: 7579. PMID: 37165035, PMCID: PMC10172370, DOI: 10.1038/s41598-023-34439-7.Peer-Reviewed Original Research
2022
Learning Correspondences of Cardiac Motion from Images Using Biomechanics-Informed Modeling
Zhang X, You C, Ahn S, Zhuang J, Staib L, Duncan J. Learning Correspondences of Cardiac Motion from Images Using Biomechanics-Informed Modeling. Lecture Notes In Computer Science 2022, 13593: 13-25. DOI: 10.1007/978-3-031-23443-9_2.Peer-Reviewed Original ResearchDisplacement vector fieldQuantitative evaluation metricsCardiac anatomical structuresTraining complexityExtensive experimentsSegmentation performanceBiomechanical feasibilityEvaluation metricsAvailable datasetsCardiac motionSmoothness constraintGeometric constraintsBiomechanical propertiesDatasetMRI dataPlausible transformationsMotionConstraintsAnatomical structuresRegularizerRegularization schemeMethodIncompressibilityImagesMetrics
2018
2-Channel Convolutional 3D Deep Neural Network (2CC3D) for FMRI Analysis: ASD Classification and Feature Learning
Li X, Dvornek NC, Papademetris X, Zhuang J, Staib LH, Ventola P, Duncan JS. 2-Channel Convolutional 3D Deep Neural Network (2CC3D) for FMRI Analysis: ASD Classification and Feature Learning. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2018, 2018: 1252-1255. PMID: 32983370, PMCID: PMC7519578, DOI: 10.1109/isbi.2018.8363798.Peer-Reviewed Original ResearchConvolutional neural networkNeural networkCNN convolutional layerSpatial featuresASD classificationDeep neural networksMean F-scoreTraditional machineFeature learningConvolutional layersInput formatF-scoreClassification modelTemporal informationNetworkWindow parametersImagesClassificationConvolutionalTemporal statisticsMachineLearningFeaturesFormatScheme
2011
AUGMENTED INLINE-BASED NAVIGATION FOR STEREOTACTIC IMAGE GUIDED NEUROSURGERY
Joshi A, Scheinost D, Globinsky R, Vives K, Spencer D, Staib L, Papademetris X. AUGMENTED INLINE-BASED NAVIGATION FOR STEREOTACTIC IMAGE GUIDED NEUROSURGERY. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2011, 1869-1872. PMID: 23377314, PMCID: PMC3557840, DOI: 10.1109/isbi.2011.5872772.Peer-Reviewed Original ResearchNovel interactive visualization techniqueInteractive visualization techniquesImage Guided NeurosurgeryComputer-assisted surgery systemVirtual landmarksImage-guided neurosurgeryVisualization techniquesCorresponding anatomical landmarksSurgery systemKey problemNavigationSurgical toolsImagesExpert evaluationFunctional areasRealtimeLandmarksVisualizationSpecific locationsAnatomical landmarksSuch locationsRepresentationToolFeedbackIntegrated Parcellation and Normalization Using DTI Fasciculography
Ho HP, Wang F, Papademetris X, Blumberg HP, Staib LH. Integrated Parcellation and Normalization Using DTI Fasciculography. Lecture Notes In Computer Science 2011, 14: 33-41. PMID: 21995010, PMCID: PMC3701295, DOI: 10.1007/978-3-642-23629-7_5.Peer-Reviewed Original ResearchConceptsDiffusion magnetic resonance imagesExtensive human interventionCumulative tracking errorsInteractive speedHuman interventionOrientation informationImage noiseMagnetic resonance imagesTracking errorVirtual pathwaysNormalization methodImagesDiffusion imagesWhite matter fasciclesFiber trackingCross-subject statisticsResonance imagesNew techniqueTrackingErrorVisualizationImplementationConnectivityInformationParcellation
2010
Integrated Segmentation and Nonrigid Registration for Application in Prostate Image-Guided Radiotherapy
Lu C, Chelikani S, Chen Z, Papademetris X, Staib LH, Duncan JS. Integrated Segmentation and Nonrigid Registration for Application in Prostate Image-Guided Radiotherapy. Lecture Notes In Computer Science 2010, 13: 53-60. PMID: 20879214, DOI: 10.1007/978-3-642-15705-9_7.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsHumansImaging, Three-DimensionalMaleProstatic NeoplasmsRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedRadiotherapy, Computer-AssistedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueSystems IntegrationTomography, X-Ray ComputedConceptsManual segmentationAutomatic segmentationImportant treatment parametersNonrigid registrationImage-guided radiotherapy systemReal patient dataNon-rigid registrationIntegrated SegmentationRegistration partRadiotherapy linear acceleratorSegmentationTreatment imagesImage qualityCone-beam CTTreatment parametersImagesPromising resultsPatient dataKey anatomical structuresLinear acceleratorRegistrationPrevious workRadiotherapy system
2009
From medical image computing to computer‐aided intervention: development of a research interface for image‐guided navigation
Papademetris X, DeLorenzo C, Flossmann S, Neff M, Vives KP, Spencer DD, Staib LH, Duncan JS. From medical image computing to computer‐aided intervention: development of a research interface for image‐guided navigation. International Journal Of Medical Robotics And Computer Assisted Surgery 2009, 5: 147-157. PMID: 19301361, PMCID: PMC2796181, DOI: 10.1002/rcs.241.Peer-Reviewed Original ResearchConceptsResearch interfaceNavigation systemApplication programming interfaceDual computer systemComputer-aided interventionsSurgery navigation systemImage-guided navigation systemProgramming interfaceClient programNetwork interfacesMedical imagesImage-guided navigationResearch softwareReal timeViable solutionSoftwareImage analysis softwareTool positionVersatile linkAnalysis softwareImagesInterfaceNavigationSystemResearch techniques
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 shapesInformationImagesSegmentation of 3D Deformable Objects with Level Set Based Prior Models
Yang J, Tagare HD, Staib LH, Duncan JS. Segmentation of 3D Deformable Objects with Level Set Based Prior Models. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2004, 1: 85-88. PMID: 20300448, PMCID: PMC2840654, DOI: 10.1109/isbi.2004.1398480.Peer-Reviewed Original ResearchMultiple objectsMedical imagesObject shapeExplicit point correspondencesShape prior constraintVariation of objectsTraining imagesMultidimensional dataTraining phaseDeformable modelDeformable objectsPoint correspondencesSegmentationPrior constraintsPrior informationLevel set functionPrior modelEstimation modelImagesObjectsLevel setsSet functionMaximum ARepresentationPoint distribution
2003
Entropy-Based Dual-Portal-to-3-DCT Registration Incorporating Pixel Correlation
Bansal R, Staib LH, Chen Z, Rangarajan A, Knisely J, Nath R, Duncan JS. Entropy-Based Dual-Portal-to-3-DCT Registration Incorporating Pixel Correlation. IEEE Transactions On Medical Imaging 2003, 22: 29. PMID: 12703758, DOI: 10.1109/tmi.2002.806430.Peer-Reviewed Original ResearchConceptsRegistration frameworkImage dataMutual information-based registration algorithmRegistration parametersPortal imagesUltrasound image dataReal patient dataTomography image dataImage pixelsPixel correlationRegistration algorithmPatient setup verificationSegmentationPixel intensityMarkov random processInitial versionTransformation parametersAppropriate entropyImagesAlgorithmPatient dataFrameworkCT imagesLine processSetup verificationNeighbor-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 distributionFrameworkComputing 3D Non-rigid Brain Registration Using Extended Robust Point Matching for Composite Multisubject fMRI Analysis
Papademetris X, Jackowski A, Schultz R, Staib L, Duncan J. Computing 3D Non-rigid Brain Registration Using Extended Robust Point Matching for Composite Multisubject fMRI Analysis. Lecture Notes In Computer Science 2003, 2879: 788-795. DOI: 10.1007/978-3-540-39903-2_96.Peer-Reviewed Original ResearchRobust Point MatchingIntensity-based registrationLarge point setsPoint matchingGreater computational efficiencyComputational efficiencyRobust pointSuperior performancePoint setsMagnetic resonance imagesBrain registrationActivation mapsFunctional magnetic resonance imagesSuccessful applicationRegistrationResonance imagesAlgorithmMatchingSpecificationMethodologyImagesRobustnessFrameworkSpecific areasSet
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
PathMaster
Mattie M, Staib L, Stratmann E, Tagare H, Duncan J, Miller P. PathMaster. Journal Of The American Medical Informatics Association 2000, 7: 404-415. PMID: 10887168, PMCID: PMC61444, DOI: 10.1136/jamia.2000.0070404.Peer-Reviewed Original ResearchConceptsDigital image databaseText-based descriptionsFeature extraction routineImage databaseIndexing methodSearch enginesFeature extractionCytopathology imagesCross-reference analysisExtraction routinesImagesPrognostic processInformation contentDescriptorsIndividual cell characteristicsDatabaseCell descriptorsRoutinesRecognition trialsEngineIndex dataExtractionMethodDescription
1999
A New Approach to 3D Sulcal Ribbon Finding from MR Images
Zeng X, Staib L, Schultz R, Tagare H, Win L, Duncan J. A New Approach to 3D Sulcal Ribbon Finding from MR Images. Lecture Notes In Computer Science 1999, 1679: 148-157. DOI: 10.1007/10704282_16.Peer-Reviewed Original ResearchGeneral segmentation methodsMR brain imagesDistance functionLittle manual interventionDeformable surface modelSegmentation workSegmentation methodManual interventionNew approachBrain imagesContour modelCortex segmentationDynamic programmingLevel setsNatural followImagesMR imagesControl problemSurface modelSegmentationQuantitative resultsProgrammingEntropy-Based, Multiple-Portal-to-3DCT Registration for Prostate Radiotherapy Using Iteratively Estimated Segmentation
Bansal R, Staib L, Chen Z, Rangarajan A, Knisely J, Nath R, Duncan J. Entropy-Based, Multiple-Portal-to-3DCT Registration for Prostate Radiotherapy Using Iteratively Estimated Segmentation. Lecture Notes In Computer Science 1999, 1679: 567-578. DOI: 10.1007/10704282_61.Peer-Reviewed Original ResearchPatient setup verificationPortal imagesReal patient dataSingle portal imagePose parametersCT data setsRegistration frameworkRegistration parametersSetup verificationDifferent initializationsAlgorithmMultiple portalsIterative fashionData setsTransformation parametersAppropriate entropyImagesCT dataPatient dataVerificationNoise conditionsFrameworkSegmentationAccurate estimationInitializationSegmentation and measurement of the cortex from 3-D MR images using coupled-surfaces propagation
Zeng X, Staib L, Schultz R, Duncan J. Segmentation and measurement of the cortex from 3-D MR images using coupled-surfaces propagation. IEEE Transactions On Medical Imaging 1999, 18: 927-937. PMID: 10628952, DOI: 10.1109/42.811276.Peer-Reviewed Original ResearchConceptsImage-derived informationEasy initializationAutomatic segmentationEfficient segmentationMR imagesChallenging problemFinal representationManual segmentationThree-dimensional MR imagesSegmentationComputational efficiencyOutermost thin layerSuch problemsImagesTight couplingNew approachConvoluted natureRepresentationGeometric measurementsInitializationImplementationSulcal foldsBrain anatomyInformationConstraints
1998
Segmentation and measurement of the cortex from 3D MR images
Zeng X, Staib L, Schultz R, Duncan J. Segmentation and measurement of the cortex from 3D MR images. Lecture Notes In Computer Science 1998, 1496: 519-530. DOI: 10.1007/bfb0056237.Peer-Reviewed Original ResearchReal 3D MR imagesImage-derived informationEasy initializationAutomatic segmentationEfficient segmentationMR imagesChallenging problemFinal representationManual segmentationSegmentationComputational efficiencyOutermost thin layerImagesTight couplingNew approachConvoluted natureRepresentationGeometric measurementsInitializationSurface propagationImplementationBrain anatomyInformationConstraintsMethodA novel approach for the registration of 2D portal and 3D CT images for treatment setup verification in radiotherapy
Bansal R, Staib L, Chen Z, Rangarajan A, Knisely J, Nath R, Duncan J. A novel approach for the registration of 2D portal and 3D CT images for treatment setup verification in radiotherapy. Lecture Notes In Computer Science 1998, 1496: 1075-1086. DOI: 10.1007/bfb0056297.Peer-Reviewed Original ResearchRegistration parametersMulti-modality image registrationResolution imagesPortal imagesLow-resolution imagesMutual information metricHigh-resolution imagesImage registrationCT data setsSetup verificationLow contrastInformation metricData setsDifficult problemLow resolutionNovel approachImagesAlgorithmCT dataRegistrationCT imagesVerificationEntropy algorithmSegmentionMetrics