2022
Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment
Petersen G, Shatalov J, Verma T, Brim WR, Subramanian H, Brackett A, Bahar RC, Merkaj S, Zeevi T, Staib LH, Cui J, Omuro A, Bronen RA, Malhotra A, Aboian MS. Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment. American Journal Of Neuroradiology 2022, 43: 526-533. PMID: 35361577, PMCID: PMC8993193, DOI: 10.3174/ajnr.a7473.Peer-Reviewed Original ResearchMeSH KeywordsGliomaHumansLymphomaMachine LearningMagnetic Resonance ImagingReproducibility of ResultsConceptsMachine learning-based methodsLearning-based methodsBalanced data setData setsVector machine modelMachine learningClassification algorithmsMachine modelMachineAlgorithmData basesPrediction modelPromising resultsPrimary CNS lymphomaPrediction model study RiskRisk of biasRadiomic featuresClassifierSetCNS lymphomaWebLearningFeaturesQualitySystematic review
2019
Scoring of Coronary Artery Disease Characteristics on Coronary CT Angiograms by Using Machine Learning
Johnson KM, Johnson HE, Zhao Y, Dowe DA, Staib LH. Scoring of Coronary Artery Disease Characteristics on Coronary CT Angiograms by Using Machine Learning. Radiology 2019, 292: 182061. PMID: 31237495, DOI: 10.1148/radiol.2019182061.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overComputed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseCoronary VesselsFemaleHumansImage Interpretation, Computer-AssistedMachine LearningMaleMiddle AgedPredictive Value of TestsReproducibility of ResultsRisk FactorsSeverity of Illness IndexYoung AdultConceptsCoronary CT angiographyCoronary Artery Disease ReportingNonfatal myocardial infarctionHeart disease deathCT angiographyCause mortalityDisease deathsMyocardial infarctionCoronary heart disease deathDisease reportingCoronary artery diseaseNational Death IndexData System scoreCardiovascular eventsCoronary deathAdverse eventsArtery diseaseCoronary diseaseDeath IndexCoronary segmentsPrognostic informationVessel scorePatientsSystem scoreSubsequent death
2016
Magnetic Resonance Imaging and Sonography in the Diagnosis of Placental Invasion
Balcacer P, Pahade J, Spektor M, Staib L, Copel JA, McCarthy S. Magnetic Resonance Imaging and Sonography in the Diagnosis of Placental Invasion. Journal Of Ultrasound In Medicine 2016, 35: 1445-1456. PMID: 27229131, DOI: 10.7863/ultra.15.07040.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 ResearchUtility of Magnetic Resonance Imaging in the Evaluation of Intraoperatively Confirmed Pelvic Adhesions
Macer ML, Mathur M, Spektor M, Gysler S, Staib L, Kodaman P, McCarthy S. Utility of Magnetic Resonance Imaging in the Evaluation of Intraoperatively Confirmed Pelvic Adhesions. Journal Of Computer Assisted Tomography 2015, 39: 896-900. PMID: 26466105, DOI: 10.1097/rct.0000000000000302.Peer-Reviewed Original ResearchConceptsMagnetic resonance imagingPelvic adhesionsPositive predictive valuePredictive valueResonance imagingSpecificity of MRIGynecologic abdominal surgeryInstitutional review board-approved retrospective analysisNegative predictive valueAnterior culPosterior culAbdominal surgeryOperative reportsInclusion criteriaRetrospective analysisStudy populationBlinded specialistsMRI sensitivityPatientsImaging
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
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 ResearchMeSH KeywordsAlgorithmsBiomechanical PhenomenaBrainGame TheoryHumansImaging, Three-DimensionalModels, NeurologicalPhantoms, ImagingReproducibility of ResultsSkullSurgery, Computer-AssistedConceptsLinear 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 applicationEarly assessment of the efficacy of digital infrared thermal imaging in pediatric extremity trauma
Silva CT, Naveed N, Bokhari S, Baker KE, Staib LH, Ibrahim SM, Muchantef K, Goodman TR. Early assessment of the efficacy of digital infrared thermal imaging in pediatric extremity trauma. Emergency Radiology 2012, 19: 203-209. PMID: 22362422, DOI: 10.1007/s10140-012-1027-2.Peer-Reviewed Original ResearchConceptsPediatric extremity traumaExtremity traumaSite of painPediatric emergency departmentSite of injuryPain sitesEmergency departmentLimb traumaContralateral limbExtremity radiographsFracture sitePatientsFurther evaluationRadiographsTraumaSame dayEarly assessmentWhole limbIntellectual disabilityLocal hyperthermiaYoung childrenDITIEfficacyLimbFracturesSimultaneous 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 toolAn integrated approach to segmentation and nonrigid registration for application in image-guided pelvic radiotherapy
Lu C, Chelikani S, Papademetris X, Knisely JP, Milosevic MF, Chen Z, Jaffray DA, Staib LH, Duncan JS. An integrated approach to segmentation and nonrigid registration for application in image-guided pelvic radiotherapy. Medical Image Analysis 2011, 15: 772-785. PMID: 21646038, PMCID: PMC3164526, DOI: 10.1016/j.media.2011.05.010.Peer-Reviewed Original ResearchAlgorithmsBayes TheoremFemaleHumansImaging, Three-DimensionalMaleProstatic NeoplasmsRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedRadiotherapy, Computer-AssistedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueSystems IntegrationTomography, X-Ray ComputedUterine Cervical NeoplasmsIntegrated 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
Image-Guided Intraoperative Cortical Deformation Recovery Using Game Theory: Application to Neocortical Epilepsy Surgery
DeLorenzo C, Papademetris X, Staib LH, Vives KP, Spencer DD, Duncan JS. Image-Guided Intraoperative Cortical Deformation Recovery Using Game Theory: Application to Neocortical Epilepsy Surgery. IEEE Transactions On Medical Imaging 2010, 29: 322-338. PMID: 20129844, PMCID: PMC2824434, DOI: 10.1109/tmi.2009.2027993.Peer-Reviewed Original ResearchConceptsDeformation estimationSurface deformationBrain surface deformationSurface deformation estimationPreoperative brain imagesCortical surface deformationSurface trackingCamera calibration parametersDisplacement errorStereo vision systemBrain deformationDeformationCalibration parametersBiomechanical modelIntraoperative brainCalibration errorsPhysical processesVision systemVivo casesCamera calibrationStereo systemInitial conditionsImage acquisitionErrorEstimationIntegrated 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
Constrained non-rigid registration for use in image-guided adaptive radiotherapy
Greene WH, Chelikani S, Purushothaman K, Knisely JP, Chen Z, Papademetris X, Staib LH, Duncan JS. Constrained non-rigid registration for use in image-guided adaptive radiotherapy. Medical Image Analysis 2009, 13: 809-817. PMID: 19682945, PMCID: PMC2771756, DOI: 10.1016/j.media.2009.07.004.Peer-Reviewed Original ResearchAlgorithmsArtificial IntelligenceHumansMalePattern Recognition, AutomatedProstatic NeoplasmsRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedRadiotherapy, Computer-AssistedRadiotherapy, ConformalReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueTomography, X-Ray ComputedUsing 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 structure
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 Research