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
2012
A Dynamical Appearance Model Based on Multiscale Sparse Representation: Segmentation of the Left Ventricle from 4D Echocardiography
Huang X, Dione DP, Compas CB, Papademetris X, Lin BA, Sinusas AJ, Duncan JS. A Dynamical Appearance Model Based on Multiscale Sparse Representation: Segmentation of the Left Ventricle from 4D Echocardiography. Lecture Notes In Computer Science 2012, 15: 58-65. PMID: 23286114, PMCID: PMC3889160, DOI: 10.1007/978-3-642-33454-2_8.Peer-Reviewed Original ResearchConceptsStatistical modelAppearance modelSparse representationIntensity modelPriorsShape predictionRepresentation methodMultiscale sparse representationSpatio-temporal coherenceSparse representation methodLocal appearanceImage sequencesModelRepresentationAppearance informationCoherenceRobustnessSegmentation accuracyPrecise Segmentation of Multiple Organs in CT Volumes Using Learning-Based Approach and Information Theory
Lu C, Zheng Y, Birkbeck N, Zhang J, Kohlberger T, Tietjen C, Boettger T, Duncan JS, Zhou SK. Precise Segmentation of Multiple Organs in CT Volumes Using Learning-Based Approach and Information Theory. Lecture Notes In Computer Science 2012, 15: 462-469. PMID: 23286081, DOI: 10.1007/978-3-642-33418-4_57.Peer-Reviewed Original ResearchConceptsMarginal Space LearningCT volumesChallenging segmentation problemInformation-theoretic schemesLearning-based approachComputer-aided diagnosisExcellent segmentation accuracyRobust boundary detectionInformation theoryPelvic organ segmentationSteerable featuresChallenging datasetArt solutionsOrgan segmentationSegmentation problemSpace learningSegmentation performanceSegmentation accuracyPrecise segmentationBoundary detectionJensen-Shannon divergenceTheoretic schemeInference processDiverse sourcesPrevious state