2024
Prior knowledge-guided vision-transformer-based unsupervised domain adaptation for intubation prediction in lung disease at one week
Yang J, Henao J, Dvornek N, He J, Bower D, Depotter A, Bajercius H, de Mortanges A, You C, Gange C, Ledda R, Silva M, Dela Cruz C, Hautz W, Bonel H, Reyes M, Staib L, Poellinger A, Duncan J. Prior knowledge-guided vision-transformer-based unsupervised domain adaptation for intubation prediction in lung disease at one week. Computerized Medical Imaging And Graphics 2024, 118: 102442. PMID: 39515190, DOI: 10.1016/j.compmedimag.2024.102442.Peer-Reviewed Original ResearchUnsupervised domain adaptationSpatial prior informationDomain adaptationLabeled dataData-driven approachUnsupervised domain adaptation modelMedical image analysis tasksImage analysis tasksTransformer-based modelsMedical image analysisPrior informationOutcome prediction tasksAdversarial trainingDistribution alignmentDomain shiftAttention headsClass tokenPoor generalizationAnalysis tasksTarget domainPrediction taskData distributionKnowledge-guidedLocal weightsMedical imagesMine yOur owN Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels
You C, Dai W, Liu F, Min Y, Dvornek N, Li X, Clifton D, Staib L, Duncan J. Mine yOur owN Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels. IEEE Transactions On Pattern Analysis And Machine Intelligence 2024, 46: 11136-11151. PMID: 39269798, DOI: 10.1109/tpami.2024.3461321.Peer-Reviewed Original ResearchMedical image segmentationImage segmentationMedical image segmentation frameworkContext of medical image segmentationLong-tailed class distributionStrong data augmentationsIntra-class variationsSemi-supervised settingData imbalance issueImage segmentation frameworkMedical image analysisMedical image dataSupervision signalsContrastive learningBenchmark datasetsUnsupervised mannerLabel setsData augmentationSegmentation frameworkDomain expertisePseudo-codeImbalance issueModel trainingMedical imagesSegmentation model
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 issue
2022
SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation
You C, Zhou Y, Zhao R, Staib L, Duncan JS. SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation. IEEE Transactions On Medical Imaging 2022, 41: 2228-2237. PMID: 35320095, PMCID: PMC10325835, DOI: 10.1109/tmi.2022.3161829.Peer-Reviewed Original ResearchConceptsMedical image segmentationImage segmentationSemi-supervised medical image segmentationRobust Medical Image SegmentationMedical image analysisUnsupervised training strategyAtrial Segmentation ChallengeLearning-based approachMedical image synthesisAverage Dice scoreSemi-supervised approachPair-wise similarityContrastive objectiveData augmentationSegmentation challengePopular datasetsDice scoreSemantic informationDistillation frameworkSegmentation accuracyDownstream tasksImage synthesisPrevious best resultSupervised counterpartMedical data
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
2011
Unified Framework for Development, Deployment and Robust Testing of Neuroimaging Algorithms
Joshi A, Scheinost D, Okuda H, Belhachemi D, Murphy I, Staib LH, Papademetris X. Unified Framework for Development, Deployment and Robust Testing of Neuroimaging Algorithms. Neuroinformatics 2011, 9: 69-84. PMID: 21249532, PMCID: PMC3066099, DOI: 10.1007/s12021-010-9092-8.Peer-Reviewed Original ResearchConceptsUser interface controlsUser interfaceNovel object-oriented frameworkCommand-line user interfaceGraphical user interface controlsMedical image analysisObject-oriented frameworkComplex image analysisImage analysisPlatform interoperabilitySoftware objectsReusable componentsInterface controlSource codeSuch algorithmsFramework idealMultiple platformsUnified frameworkAlgorithmRapid developmentDeploymentThorough testingPublic useFrameworkPlatform
1998
Volumetric layer segmentation using coupled surfaces propagation
Zeng X, Staib L, Schultz R, Duncan J. Volumetric layer segmentation using coupled surfaces propagation. 2015 IEEE Conference On Computer Vision And Pattern Recognition (CVPR) 1998, 708-715. DOI: 10.1109/cvpr.1998.698681.Peer-Reviewed Original ResearchMedical image analysisUseful image informationMagnetic resonance brain imagesImage-derived informationImage gradient informationLevel set implementationGray level valuesEasy initializationSegmentation problemImage informationAutomatic segmentationGradient informationSet implementationBrain imagesLayer segmentationComputational efficiencyNon-brain structuresLeft ventricle myocardiumImage analysisSegmentationInformationNew approachTest examplesSurface propagationVentricle myocardium
1990
Medical image analysis using model-based optimization
Duncan J, Staib L, Birkholzer T, Owen R, Anandan P, Bozma I. Medical image analysis using model-based optimization. 1990, 370-377. DOI: 10.1109/vbc.1990.109344.Peer-Reviewed Original ResearchMedical image analysisObject recognition problemOutlines of objectsModel-based optimizationRecognition problemExtracting featuresSegmented objectsOptimization theoryMathematical modelMedical imagingObject shapeUnifying approachAnalysis problemImage analysisThird exampleQuantitative descriptionObjectsMovement propertiesProblemSegmentationAnalysis methodPurpose of diagnosisOptimizationExampleMotion