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. 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
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
2018
Prediction of Severity and Treatment Outcome for ASD from fMRI
Zhuang J, Dvornek NC, Li X, Ventola P, Duncan JS. Prediction of Severity and Treatment Outcome for ASD from fMRI. Lecture Notes In Computer Science 2018, 11121: 9-17. PMID: 32984867, PMCID: PMC7513883, DOI: 10.1007/978-3-030-00320-3_2.Peer-Reviewed Original ResearchFeature selectionMedical image analysis problemsMedical image analysisLimited training examplesImage analysis problemsDimension of dataFeature selection methodHigh-dimensional regression problemsTraining examplesTwo-level approachAccurate predictive modelsRegression problemsHigh dimensionalityLarge databaseRandom forest modelSelection methodNon-linear caseAnalysis problemNumber of voxelsImage analysisForest modelState fMRI datasetsMeans of voxelAccurate modelFMRI datasets