2024
In vivo neuropil density from anatomical MRI and machine learning
Akif A, Staib L, Herman P, Rothman D, Yu Y, Hyder F. In vivo neuropil density from anatomical MRI and machine learning. Cerebral Cortex 2024, 34: bhae200. PMID: 38771239, PMCID: PMC11107380, DOI: 10.1093/cercor/bhae200.Peer-Reviewed Original ResearchConceptsMagnetic resonance imagingSynaptic densityNeuropil densityCellular densityArtificial neural networkNeural networkPositron emission tomographyAnatomical magnetic resonance imagingHealthy subjectsSynaptic activityMRI scansMachine learning algorithmsBrain's energy budgetEmission tomographyIn vivo MRI scansResonance imagingTissue cellularityLearning algorithmsDiffusion magnetic resonance imagingMachine learningMicroscopic interpretationInterpretation of functional neuroimaging dataIndividual predictionsSubjects
2021
BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis
Li X, Zhou Y, Dvornek N, Zhang M, Gao S, Zhuang J, Scheinost D, Staib LH, Ventola P, Duncan JS. BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis. Medical Image Analysis 2021, 74: 102233. PMID: 34655865, PMCID: PMC9916535, DOI: 10.1016/j.media.2021.102233.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagesGraph neural network frameworkMedical image analysisGraph neural networkGraph convolutional layersNeural network frameworkDifferent evaluation metricsSpecific task statesIndependent fMRI datasetsPooling layerConvolutional layersConsistency lossNetwork frameworkNeural networkFMRI datasetsImage analysis methodEvaluation metricsDetection resultsBrain graphsSubjects releaseROI selectionImage analysisCognitive stimuliTask statesFMRI analysis
2020
Sparse Data–Driven Learning for Effective and Efficient Biomedical Image Segmentation
Onofrey JA, Staib LH, Huang X, Zhang F, Papademetris X, Metaxas D, Rueckert D, Duncan JS. Sparse Data–Driven Learning for Effective and Efficient Biomedical Image Segmentation. Annual Review Of Biomedical Engineering 2020, 22: 1-27. PMID: 32169002, PMCID: PMC9351438, DOI: 10.1146/annurev-bioeng-060418-052147.Peer-Reviewed Original Research
2018
Segmenting the Brain Surface From CT Images With Artifacts Using Locally Oriented Appearance and Dictionary Learning
Onofrey JA, Staib LH, Papademetris X. Segmenting the Brain Surface From CT Images With Artifacts Using Locally Oriented Appearance and Dictionary Learning. IEEE Transactions On Medical Imaging 2018, 38: 596-607. PMID: 30176584, PMCID: PMC6476428, DOI: 10.1109/tmi.2018.2868045.Peer-Reviewed Original Research
2016
Brain responses to biological motion predict treatment outcome in young children with autism
Yang D, Pelphrey KA, Sukhodolsky DG, Crowley MJ, Dayan E, Dvornek NC, Venkataraman A, Duncan J, Staib L, Ventola P. Brain responses to biological motion predict treatment outcome in young children with autism. Translational Psychiatry 2016, 6: e948-e948. PMID: 27845779, PMCID: PMC5314125, DOI: 10.1038/tp.2016.213.Peer-Reviewed Original ResearchConceptsAutism spectrum disorderYoung childrenSocial information processingMultivariate pattern analysisMotivation/rewardBiological motionCore deficitComplex neurodevelopmental disorderBrain responsesResponse treatmentSpectrum disorderNeurobiological markersNeural predictorsInformation processingBehavioral interventionsIndividual childrenNeurodevelopmental disordersCurrent findingsNeural circuitsBehavioral deficitsEarly childhoodChildrenUnsuccessful interventionsNeurobiomarkersPattern analysisPivotal response treatment prompts a functional rewiring of the brain among individuals with autism spectrum disorder
Venkataraman A, Yang D, Dvornek N, Staib LH, Duncan JS, Pelphrey KA, Ventola P. Pivotal response treatment prompts a functional rewiring of the brain among individuals with autism spectrum disorder. Neuroreport 2016, 27: 1081-1085. PMID: 27532879, PMCID: PMC5007196, DOI: 10.1097/wnr.0000000000000662.Peer-Reviewed Original ResearchConceptsPivotal Response TreatmentAutism spectrum disorderOccipital-temporal cortexAttentional systemResponse treatmentSpectrum disorderOrbitofrontal cortexPosterior cingulateHigh-level objectsBehavioral interventionsLearning mechanismPerception shiftProcessing areasNeural circuitsFunctional rewiringCortexTreatment regimenAutismInterventionNovel Bayesian frameworkCingulateFunctional changesIndividualsDisordersObjects
2015
Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients
Onofrey JA, Staib LH, Papademetris X. Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients. NeuroImage Clinical 2015, 10: 291-301. PMID: 26900569, PMCID: PMC4724039, DOI: 10.1016/j.nicl.2015.12.001.Peer-Reviewed Original ResearchSegmenting 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
2012
Anatomical Brain Images Alone Can Accurately Diagnose Chronic Neuropsychiatric Illnesses
Bansal R, Staib LH, Laine AF, Hao X, Xu D, Liu J, Weissman M, Peterson BS. Anatomical Brain Images Alone Can Accurately Diagnose Chronic Neuropsychiatric Illnesses. PLOS ONE 2012, 7: e50698. PMID: 23236384, PMCID: PMC3517530, DOI: 10.1371/journal.pone.0050698.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAlgorithmsAttention Deficit Disorder with HyperactivityBipolar DisorderBrainChildDepressive Disorder, MajorFemaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedReproducibility of ResultsSchizophreniaSensitivity and SpecificityTourette SyndromeConceptsBrains of personsNeuropsychiatric illnessBrain regionsNeuropsychiatric disordersMRI scansMajor depressive disorderChronic neuropsychiatric disorderAttention-deficit/hyperactivity disorderSpecific neuropsychiatric disordersDifferent neuropsychiatric disordersLarge MRI datasetsAnatomical MRI scansDisease courseCerebral cortexLow familial riskDepressive disorderBiological subtypesTourette syndromeBipolar disorderAnatomical brain imagesClinical diagnosisFamilial riskIllnessDiagnostic accuracyDiagnostic algorithmVolumetric Intraoperative Brain Deformation Compensation: Model Development and Phantom Validation
DeLorenzo C, Papademetris X, Staib LH, Vives KP, Spencer DD, Duncan JS. Volumetric Intraoperative Brain Deformation Compensation: Model Development and Phantom Validation. IEEE Transactions On Medical Imaging 2012, 31: 1607-1619. PMID: 22562728, PMCID: PMC3600363, DOI: 10.1109/tmi.2012.2197407.Peer-Reviewed Original ResearchConceptsLinear elastic modelSurface displacementsElastic modelBrain deformationVolumetric brain deformationMaterial parametersMaterial propertiesRealistic brain phantomDeformationBiomechanical modelIntraoperative brainModel accuracyLocalization errorPhantom validationAccurate surgical guidanceModel solutionsModel developmentInitial estimationDisplacementModel sensitivityQuantitative validationPhantom resultsPreoperative imagesSurgical guidancePreliminary application
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 toolIntegrated 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
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
Using 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 ResearchBayesian 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
Voxel-wise comparisons of the morphology of diffusion tensors across groups of experimental subjects
Bansal R, Staib LH, Plessen KJ, Xu D, Royal J, Peterson BS. Voxel-wise comparisons of the morphology of diffusion tensors across groups of experimental subjects. Psychiatry Research 2007, 156: 225-245. PMID: 18006284, PMCID: PMC2215316, DOI: 10.1016/j.pscychresns.2006.12.015.Peer-Reviewed Original ResearchConceptsApproximate covariance matrixRespective true valuesScalar measureMathematical frameworkMultivariate GaussianCovariance matrixMean eigenvaluesTensor morphologyEigenvaluesDelta methodEigenvectorsOrthogonal vectorsDiffusion tensorTensor eigenvectorsScalar magnitudeNonlinear wayTensorTrue valueGaussianComplex 3D morphologyDT dataAnisotropyNeuroanatomical connectivityProbabilityDirectionStatistical 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
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