2024
Coordinate-Independent 3-D Ultrasound Principal Stretch and Direction Imaging
Jeng G, Chen P, Hsieh M, Liu Z, Langdon J, Ahn S, Staib L, Stendahl J, Thorn S, Sinusas A, Duncan J, O'Donnell M. Coordinate-Independent 3-D Ultrasound Principal Stretch and Direction Imaging. IEEE Transactions On Biomedical Engineering 2024, PP: 1-12. PMID: 38941195, DOI: 10.1109/tbme.2024.3420220.Peer-Reviewed Original ResearchPrincipal stretchesAxial displacement componentsSpeckle tracking methodSpeckle tracking approachTracking methodRobust filterDisplacement componentsTissue incompressibilityDisplacement estimationStrain componentsDisplacement gradientsStrain informationLocalized diseased regionStrain imagingLagrangian strainLeast-squares methodTracking approachTracking frameworkCoordinate systemCardiac coordinate systemProbe orientationFilterHigher spatial resolutionCardiac datasetsEnhanced accuracyTAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction
Guo X, Shi L, Chen X, Liu Q, Zhou B, Xie H, Liu Y, Palyo R, Miller E, Sinusas A, Staib L, Spottiswoode B, Liu C, Dvornek N. TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction. Medical Image Analysis 2024, 96: 103190. PMID: 38820677, PMCID: PMC11180595, DOI: 10.1016/j.media.2024.103190.Peer-Reviewed Original ResearchGenerative adversarial networkAdversarial networkMotion estimation accuracyInter-frame motionIntensity-based image registration techniqueAll-to-oneSegmentation masksImage registration techniquesOriginal frameTemporal informationDiagnosis accuracyMyocardial blood flowEstimation accuracyFrame conversionPositron emission tomographyNovel methodImage qualityPET datasetsRegistration techniqueNetworkCardiac positron emission tomographyBlood flowDynamic cardiac positron emission tomographyMotion correctionCoronary artery diseaseIn 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 predictionsSubjectsMulti-Task Learning for Motion Analysis and Segmentation in 3D Echocardiography
Ta K, Ahn S, Thorn S, Stendahl J, Zhang X, Langdon J, Staib L, Sinusas A, Duncan J. Multi-Task Learning for Motion Analysis and Segmentation in 3D Echocardiography. IEEE Transactions On Medical Imaging 2024, 43: 2010-2020. PMID: 38231820, DOI: 10.1109/tmi.2024.3355383.Peer-Reviewed Original ResearchMulti-task learning networkCross-stitch unitsComposite loss functionAccurate motion estimationTask-specific networksMotion estimationSegmentation masksLearning networkLoss functionSegmentation stepEchocardiography datasetNetworkMotion displacementMotion analysisMultiple time framesTaskAnalysis pipelineSegmentsStrain measurementsDatasetRepresentationMulticenter Quantification of Radiation Exposure and Associated Risks for Prostatic Artery Embolization in 1476 Patients.
Ayyagari R, Rahman S, Grizzard K, Mustafa A, Staib L, Makkia R, Bhatia S, Bilhim T, Carnevale F, Davis C, Fischman A, Isaacson A, McClure T, McWilliams J, Nutting C, Richardson A, Salem R, Sapoval M, Yu H. Multicenter Quantification of Radiation Exposure and Associated Risks for Prostatic Artery Embolization in 1476 Patients. Radiology 2024, 310: e231877. PMID: 38441098, DOI: 10.1148/radiol.231877.Peer-Reviewed Original ResearchConceptsProstatic artery embolizationCumulative air kermaRadiation-related adverse eventsBody mass indexAdverse eventsEffective doseFluoroscopy timeArtery embolizationRadiation doseKerma area product valuesMedian cumulative air kermaMedian effective radiation doseFluoroscopy unitPatient body mass indexRadiation exposureTwo-sample <i>t</i> test wasRadiation dose dataBenign prostatic hyperplasiaFluoroscopy-guided proceduresPatient radiation exposureEffective radiation doseRadiation field areaRadiation effective doseWilcoxon rank sum testInvasive angiographic proceduresReliable Prostate Cancer Risk Mapping From MRI Using Targeted and Systematic Core Needle Biopsy Histopathology
Zeevi T, Leapman M, Sprenkle P, Venkataraman R, Staib L, Onofrey J. Reliable Prostate Cancer Risk Mapping From MRI Using Targeted and Systematic Core Needle Biopsy Histopathology. IEEE Transactions On Biomedical Engineering 2024, 71: 1084-1091. PMID: 37874731, PMCID: PMC10901528, DOI: 10.1109/tbme.2023.3326799.Peer-Reviewed Original ResearchMagnetic resonance imagingIndividual patientsBiopsy locationProstate biopsy dataBiopsy histopathologyHistopathology scoresPathology scoresBiopsy dataMRI biomarkersTreatment planPatientsResonance imagingProstate regionBiomarkersTherapy treatment plansPathologyRepresentative sampleScoresImaging analysisPrevious studiesHistopathologyProstateCancerCliniciansChapter 13 Data-driven learning strategies for biomarker detection and outcome prediction in Autism from task-based fMRI
Duncan J, Staib L, Dvornek N, Li X, Zhuang J, Wang J, Ventola P. Chapter 13 Data-driven learning strategies for biomarker detection and outcome prediction in Autism from task-based fMRI. 2024, 357-393. DOI: 10.1016/b978-0-32-385124-4.00024-6.Peer-Reviewed Original ResearchLong short-term memoryGraph neural networksFunctional magnetic resonance imagingAutism spectrum disorderNeural ordinary differential equationsData-driven learning strategyDeep learning techniquesTask-based functional magnetic resonance imagingShort-term memoryNeural networkLearning techniquesImpaired social interactionTerm memoryBehavioral therapyRepetitive behaviorsSpectrum disorderDevelopmental disordersLearning strategiesSpatio-temporal characteristicsInherent dynamicsCharacterization of individualsModel of causalitySocial interactionNetworkPersonalized outcome predictions
2023
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective.
You C, Dai W, Min Y, Liu F, Clifton D, Zhou S, Staib L, Duncan J. Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective. Advances In Neural Information Processing Systems 2023, 36: 9984-10021. PMID: 38813114, PMCID: PMC11136570.Peer-Reviewed Original ResearchMedical image segmentationContrastive learningImage segmentationSemi-supervised medical image segmentationSemi-supervised contrastive learningSelf-supervised objectiveSemantic segmentation datasetsSemi-supervised methodGround-truth labelsQuality of visual representationSafety-critical tasksSegmentation datasetTail classesSegmentation taskLabel setsTruth labelsCL frameworkNegative examplesModel collapseVariance-reductionVariance-reduction techniquesVisual representationTaskLearningPairs of samplesDeferral of Estimated Glomerular Filtration Rate Testing Before Contrast-Enhanced CT in Low-Risk Emergency Department Patients: Assessment of Safety and Impact on Throughput
Gunabushanam G, Asch D, van Luling J, Kuehne A, Alkukhun A, Staib L, Venkatesh A, Pahade J. Deferral of Estimated Glomerular Filtration Rate Testing Before Contrast-Enhanced CT in Low-Risk Emergency Department Patients: Assessment of Safety and Impact on Throughput. Journal Of The American College Of Radiology 2023, 21: 52-60. PMID: 37939813, DOI: 10.1016/j.jacr.2023.11.003.Peer-Reviewed Original ResearchAcute kidney injuryChronic kidney diseaseContrast-enhanced CTLower riskED providersMedian OSEGFR testingContrast-induced acute kidney injuryLow-risk emergency department patientsLow-risk ED patientsProportion of patientsEmergency department patientsClinical risk assessmentGlomerular filtration rate testingAssessment of safetyChronic dialysisKidney injuryDepartment patientsED patientsEGFR valuesKidney diseaseRisk factorsPatientsCECT studiesRiskImplicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts
You C, Dai W, Min Y, Staib L, Duncan J. Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts. Lecture Notes In Computer Science 2023, 14222: 561-571. PMID: 38840671, PMCID: PMC11151725, DOI: 10.1007/978-3-031-43898-1_54.Peer-Reviewed Original ResearchMedical image segmentationImage segmentationSegmentation methodPixel-level featuresComputer graphics problemImplicit neural representationsGrid-based representationMedical segmentationRendering frameworkSegmentation predictionsEnd mannerCorrelated contentCompetitive performance improvementsGraphics problemsSegmentationPoint representationPerformance improvementRegular gridSuch informationRepresentationConvolution operatorsExpertsComplex signalsRenderingFeaturesACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast
You C, Dai W, Min Y, Staib L, Sekhon J, Duncan J. ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast. Lecture Notes In Computer Science 2023, 14223: 194-205. PMID: 38813456, PMCID: PMC11136572, DOI: 10.1007/978-3-031-43901-8_19.Peer-Reviewed Original ResearchLearning 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. 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 issueA Multiclass Radiomics Method–Based WHO Severity Scale for Improving COVID-19 Patient Assessment and Disease Characterization From CT Scans
Henao J, Depotter A, Bower D, Bajercius H, Todorova P, Saint-James H, de Mortanges A, Barroso M, He J, Yang J, You C, Staib L, Gange C, Ledda R, Caminiti C, Silva M, Cortopassi I, Dela Cruz C, Hautz W, Bonel H, Sverzellati N, Duncan J, Reyes M, Poellinger A. A Multiclass Radiomics Method–Based WHO Severity Scale for Improving COVID-19 Patient Assessment and Disease Characterization From CT Scans. Investigative Radiology 2023, 58: 882-893. PMID: 37493348, PMCID: PMC10662611, DOI: 10.1097/rli.0000000000001005.Peer-Reviewed Original ResearchConceptsCOVID-19 positive patientsClinical Progression ScaleLung lesionsLesion modelDisease severityGround-glass opacitiesCOVID-19 patientsRadiologist assessmentExpert thoracic radiologistsMulticenter cohortPleural effusionDisease extentRetrospective studyDevelopment cohortPatient assessmentTomography scanCT scanSeverity ScalePatient's diseaseTissue lesionsThoracic radiologistsLesionsPatientsRadiomics modelRadiomic featuresBootstrapping Semi-supervised Medical Image Segmentation with Anatomical-Aware Contrastive Distillation
You C, Dai W, Min Y, Staib L, Duncan J. Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-Aware Contrastive Distillation. Lecture Notes In Computer Science 2023, 13939: 641-653. PMID: 37409056, PMCID: PMC10322187, DOI: 10.1007/978-3-031-34048-2_49.Peer-Reviewed Original ResearchPredicting 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 ResearchIntegrating Prostate Specific Antigen Density Biomarker Into Deep Learning Prostate MRI Lesion Segmentation Models
Zhong J, Staib L, Venkataraman R, Onofrey J. Integrating Prostate Specific Antigen Density Biomarker Into Deep Learning Prostate MRI Lesion Segmentation Models. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2023, 00: 1-5. PMID: 38090633, PMCID: PMC10711801, DOI: 10.1109/isbi53787.2023.10230418.Peer-Reviewed Original Research
2022
Class-Aware Adversarial Transformers for Medical Image Segmentation.
You C, Zhao R, Liu F, Dong S, Chinchali S, Topcu U, Staib L, Duncan J. Class-Aware Adversarial Transformers for Medical Image Segmentation. Advances In Neural Information Processing Systems 2022, 35: 29582-29596. PMID: 37533756, PMCID: PMC10395073.Peer-Reviewed Original ResearchMedical image segmentationImage segmentationMedical image analysis domainMedical image analysis tasksImage analysis domainMedical image datasetsImage analysis tasksModel’s inner workingsTransformer-based approachTransformer-based modelsAdversarial training strategyRich semantic contextSegmentation label mapsLong-range dependenciesMulti-scale representationAnalysis tasksImage datasetsTransfer learningFeature representationInner workingsSegmentation accuracyCorrelated contentTransformer moduleLabel mapsInformation lossOperator Learning Curve for Prostatic Artery Embolization and Its Impact on Outcomes in 296 Patients
Powell T, Rahman S, Staib L, Bhatia S, Ayyagari R. Operator Learning Curve for Prostatic Artery Embolization and Its Impact on Outcomes in 296 Patients. CardioVascular And Interventional Radiology 2022, 46: 229-237. PMID: 36456689, DOI: 10.1007/s00270-022-03321-w.Peer-Reviewed Original ResearchIncremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation
You C, Xiang J, Su K, Zhang X, Dong S, Onofrey J, Staib L, Duncan J. Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation. Lecture Notes In Computer Science 2022, 13573: 3-16. PMID: 37415747, PMCID: PMC10323962, DOI: 10.1007/978-3-031-18523-6_1.Peer-Reviewed Original ResearchIncremental learningMedical image segmentation tasksMulti-site datasetImage segmentation tasksMedical image segmentationProstate MRI SegmentationComputation resourcesMedical datasetsSegmentation taskImage segmentationSegmentation frameworkEmbedding featuresBenchmark datasetsMRI segmentationTraining dataTarget domainLearning approachPractical deploymentDomain-specific expertiseCompetitive performanceDatasetTraining schemePrior workSegmentationSingle modelAtlas-Based Semantic Segmentation of Prostate Zones
Zhang J, Venkataraman R, Staib L, Onofrey J. Atlas-Based Semantic Segmentation of Prostate Zones. Lecture Notes In Computer Science 2022, 13435: 570-579. PMID: 38084296, PMCID: PMC10711803, DOI: 10.1007/978-3-031-16443-9_55.Peer-Reviewed Original ResearchSegmentation resultsSemantic segmentation frameworkSemantic segmentation resultsDice similarity coefficient valuesSemantic segmentationInference stageSegmentation frameworkSegmentation performanceExternal test datasetTest datasetRegion of interestSegmentationAnatomical atlasHyperparametersSimilarity coefficient valuesAnatomical informationGitHubUsersDatasetProstate zonesCodeFrameworkInformation