2024
Heteroscedastic Uncertainty Estimation Framework for Unsupervised Registration
Zhang X, Pak D, Ahn S, Li X, You C, Staib L, Sinusas A, Wong A, Duncan J. Heteroscedastic Uncertainty Estimation Framework for Unsupervised Registration. Lecture Notes In Computer Science 2024, 15002: 651-661. DOI: 10.1007/978-3-031-72069-7_61.Peer-Reviewed Original ResearchUnsupervised registrationReal-world medical imagesCollaborative training strategyMedical image datasetsDeep learning methodsAccurate displacement estimationSignal-to-noise ratioImage datasetsRegistration architectureLearning methodsMedical imagesTraining strategyNoise distributionUncertainty estimationWeighting schemeRegistration performanceSpatial domainEstimation frameworkInput-dependentUncertainty estimation frameworkUniform noise levelsDisplacement estimationFrameworkNoise levelUnsupervisedAdaptive Correspondence Scoring for Unsupervised Medical Image Registration
Zhang X, Stendahl J, Staib L, Sinusas A, Wong A, Duncan J. Adaptive Correspondence Scoring for Unsupervised Medical Image Registration. Lecture Notes In Computer Science 2024, 15096: 76-92. DOI: 10.1007/978-3-031-72920-1_5.Peer-Reviewed Original ResearchMedical image registrationAdaptation frameworkMedical image datasetsUnsupervised learning schemeAdaptive training schemeImage registrationError residualsSupervision signalsLearning schemeImage datasetsRegistration architectureIntensity constancyScore mapNoisy gradientsMedical imagesTraining schemeImage reconstructionPerformance degradationLambertian assumptionCorrespondence scoresLoss of correspondenceTraining objectivesDisplacement estimationImage acquisitionScheme
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 loss