2019
Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features
Wang CJ, Hamm CA, Savic LJ, Ferrante M, Schobert I, Schlachter T, Lin M, Weinreb JC, Duncan JS, Chapiro J, Letzen B. Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features. European Radiology 2019, 29: 3348-3357. PMID: 31093705, PMCID: PMC7243989, DOI: 10.1007/s00330-019-06214-8.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAlgorithmsBile Duct NeoplasmsBile Ducts, IntrahepaticCarcinoma, HepatocellularCholangiocarcinomaDeep LearningFemaleHumansImage Interpretation, Computer-AssistedLiver NeoplasmsMachine LearningMagnetic Resonance ImagingMaleMiddle AgedNeural Networks, ComputerPredictive Value of TestsProof of Concept StudyRetrospective StudiesConceptsDeep learning systemConvolutional neural networkLearning systemRelevance scoresFeature mapsPre-trained CNN modelsFeature relevance scoresMulti-phasic MRINeural network interpretationEvidence-based decision supportDeep NeuralDeep learningCNN modelLesion classifierLearning prototypeNeural networkOriginal imageSystem prototypeDecision supportLesion classificationNetwork interpretationImage voxelsIncorrect featuresLesion classesTest setDeep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI
Hamm CA, Wang CJ, Savic LJ, Ferrante M, Schobert I, Schlachter T, Lin M, Duncan JS, Weinreb JC, Chapiro J, Letzen B. Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI. European Radiology 2019, 29: 3338-3347. PMID: 31016442, PMCID: PMC7251621, DOI: 10.1007/s00330-019-06205-9.Peer-Reviewed Original ResearchAdultAgedBile Duct NeoplasmsBile Ducts, IntrahepaticCarcinoma, HepatocellularCholangiocarcinomaDeep LearningFemaleHumansImage Interpretation, Computer-AssistedLiver NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedNeural Networks, ComputerReproducibility of ResultsROC CurveSensitivity and SpecificityUnited States
2014
Objective comparison of particle tracking methods
Chenouard N, Smal I, de Chaumont F, Maška M, Sbalzarini IF, Gong Y, Cardinale J, Carthel C, Coraluppi S, Winter M, Cohen AR, Godinez WJ, Rohr K, Kalaidzidis Y, Liang L, Duncan J, Shen H, Xu Y, Magnusson KE, Jaldén J, Blau HM, Paul-Gilloteaux P, Roudot P, Kervrann C, Waharte F, Tinevez JY, Shorte SL, Willemse J, Celler K, van Wezel GP, Dan HW, Tsai YS, de Solórzano C, Olivo-Marin JC, Meijering E. Objective comparison of particle tracking methods. Nature Methods 2014, 11: 281-289. PMID: 24441936, PMCID: PMC4131736, DOI: 10.1038/nmeth.2808.Peer-Reviewed Original Research
2013
Contour tracking in echocardiographic sequences via sparse representation and dictionary learning
Huang X, Dione DP, Compas CB, Papademetris X, Lin BA, Bregasi A, Sinusas AJ, Staib LH, Duncan JS. Contour tracking in echocardiographic sequences via sparse representation and dictionary learning. Medical Image Analysis 2013, 18: 253-271. PMID: 24292554, PMCID: PMC3946038, DOI: 10.1016/j.media.2013.10.012.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsArtifactsDogsEchocardiographyEndocardiumHeart VentriclesImage EnhancementImage Interpretation, Computer-AssistedMyocardial InfarctionReproducibility of ResultsSensitivity and SpecificityConceptsContour trackerSparse representationEchocardiographic sequencesRegion-based level set segmentationLevel set segmentationLocal image appearanceManual tracingExpert manual tracingsMultiscale sparse representationImage sequencesSegmentation resultsAppearance modelSpatiotemporal priorsFirst frameMultilevel informationHuman data setsEjection fraction estimatesLocal appearanceImage appearanceDictionary learningShape modelContour trackingManual resultsData setsContour estimationA Multiple Hypothesis Based Method for Particle Tracking and Its Extension for Cell Segmentation
Liang L, Shen H, Rompolas P, Greco V, De Camilli P, Duncan JS. A Multiple Hypothesis Based Method for Particle Tracking and Its Extension for Cell Segmentation. Lecture Notes In Computer Science 2013, 23: 98-109. PMID: 24683961, PMCID: PMC4122512, DOI: 10.1007/978-3-642-38868-2_9.Peer-Reviewed Original ResearchSegmentation of 4D Echocardiography Using Stochastic Online Dictionary Learning
Huang X, Dione DP, Lin BA, Bregasi A, Sinusas AJ, Duncan JS. Segmentation of 4D Echocardiography Using Stochastic Online Dictionary Learning. Lecture Notes In Computer Science 2013, 16: 57-65. PMID: 24505744, DOI: 10.1007/978-3-642-40760-4_8.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsArtificial IntelligenceData Interpretation, StatisticalDogsEchocardiography, Four-DimensionalImage EnhancementImage Interpretation, Computer-AssistedMyocardial InfarctionPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificityStochastic ProcessesSubtraction Technique
2012
Simultaneous Nonrigid Registration, Segmentation, and Tumor Detection in MRI Guided Cervical Cancer Radiation Therapy
Lu C, Chelikani S, Jaffray DA, Milosevic MF, Staib LH, Duncan JS. Simultaneous Nonrigid Registration, Segmentation, and Tumor Detection in MRI Guided Cervical Cancer Radiation Therapy. IEEE Transactions On Medical Imaging 2012, 31: 1213-1227. PMID: 22328178, PMCID: PMC3889159, DOI: 10.1109/tmi.2012.2186976.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsFemaleHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingPattern Recognition, AutomatedRadiotherapy, ConformalRadiotherapy, Image-GuidedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueUterine Cervical NeoplasmsA 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 accuracy
2011
Segmentation of 3D radio frequency echocardiography using a spatio-temporal predictor
Pearlman PC, Tagare HD, Lin BA, Sinusas AJ, Duncan JS. Segmentation of 3D radio frequency echocardiography using a spatio-temporal predictor. Medical Image Analysis 2011, 16: 351-360. PMID: 22078842, PMCID: PMC3267850, DOI: 10.1016/j.media.2011.09.002.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsComputer SimulationDogsEchocardiography, Three-DimensionalHeart VentriclesImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalModels, CardiovascularModels, StatisticalPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueConceptsLeft ventricular endocardial boundarySpatio-temporal predictorsStandard level setRF dataSpatio-temporal coherenceNeighboring framesImage sequencesBoundary detectionMultiple framesImage inhomogeneitySegmentationEndocardial boundaryGeometric constraintsManual tracingRF ultrasoundAlgorithmLevel setsEchocardiographic imagesFrameConditional modelLinear predictorTrackingSpatial modelImagesRobustnessSegmentation of 3D RF Echocardiography Using a Multiframe Spatio-temporal Predictor
Pearlman PC, Tagare HD, Lin BA, Sinusas AJ, Duncan JS. Segmentation of 3D RF Echocardiography Using a Multiframe Spatio-temporal Predictor. Lecture Notes In Computer Science 2011, 22: 37-48. PMID: 21761644, DOI: 10.1007/978-3-642-22092-0_4.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsDogsEchocardiography, Three-DimensionalImage EnhancementImage Interpretation, Computer-AssistedPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificityConceptsLeft ventricular endocardial boundarySpatio-temporal predictorsStandard level setSpatio-temporal coherenceNeighboring framesImage sequencesBoundary detectionRF dataMultiple framesImage inhomogeneitySegmentationEndocardial boundaryGeometric constraintsManual tracingRF ultrasoundLevel setsConditional modelEchocardiographic imagesFrameLinear predictorAlgorithmTrackingSpatial modelImagesRobustnessA Unified Framework for Joint Segmentation, Nonrigid Registration and Tumor Detection: Application to MR-Guided Radiotherapy
Lu C, Chelikani S, Duncan JS. A Unified Framework for Joint Segmentation, Nonrigid Registration and Tumor Detection: Application to MR-Guided Radiotherapy. Lecture Notes In Computer Science 2011, 22: 525-537. PMID: 21761683, PMCID: PMC3889153, DOI: 10.1007/978-3-642-22092-0_43.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceComputer SimulationFemaleHumansImage EnhancementImage Interpretation, Computer-AssistedModels, BiologicalModels, StatisticalPattern Recognition, AutomatedRadiotherapy, Computer-AssistedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueUterine Cervical NeoplasmsNon-rigid Registration of Longitudinal Brain Tumor Treatment MRI
Chitphakdithai N, Chiang VL, Duncan JS. Non-rigid Registration of Longitudinal Brain Tumor Treatment MRI. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2011, 2011: 4893-4896. PMID: 22255435, PMCID: PMC3753806, DOI: 10.1109/iembs.2011.6091212.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBrainBrain NeoplasmsHumansImage Interpretation, Computer-AssistedLongitudinal StudiesMagnetic Resonance ImagingPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySubtraction Technique
2010
A coupled deformable model for tracking myocardial borders from real-time echocardiography using an incompressibility constraint
Zhu Y, Papademetris X, Sinusas AJ, Duncan JS. A coupled deformable model for tracking myocardial borders from real-time echocardiography using an incompressibility constraint. Medical Image Analysis 2010, 14: 429-448. PMID: 20350833, PMCID: PMC4318707, DOI: 10.1016/j.media.2010.02.005.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsArtificial IntelligenceComputer SystemsDogsEchocardiography, Three-DimensionalElasticity Imaging TechniquesHumansImage EnhancementImage Interpretation, Computer-AssistedPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueConceptsDeformable modelImage-derived informationLV endocardial boundariesImage acquisition techniquesFinal segmentationAutomatic algorithmGround truthManual segmentationVolumetric imagesSegmentationSynthetic dataEndocardial boundaryNumber of effortsMyocardial bordersEpicardial boundariesAcquisition techniquesInstantaneous acquisitionConstraintsImagesEchocardiographic imagesSetSpeckle statisticsAlgorithmReal-time echocardiographyNon-rigid Registration with Missing Correspondences in Preoperative and Postresection Brain Images
Chitphakdithai N, Duncan JS. Non-rigid Registration with Missing Correspondences in Preoperative and Postresection Brain Images. Lecture Notes In Computer Science 2010, 13: 367-374. PMID: 20879252, PMCID: PMC3031159, DOI: 10.1007/978-3-642-15705-9_45.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBrainHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueConceptsTypes of datasetsNon-rigid registration methodImage alignmentNon-rigid registrationMissing correspondencesSegmentation algorithmNon-rigid registration algorithmSimilarity metricCorrespondence problemValid correspondencesRegistration algorithmRegistration methodExpectation-maximization algorithmBrain imagesJoint registrationReal dataAlgorithmImagesRegistrationError kernel3D Radio Frequency Ultrasound Cardiac Segmentation Using a Linear Predictor
Pearlman PC, Tagare HD, Sinusas AJ, Duncan JS. 3D Radio Frequency Ultrasound Cardiac Segmentation Using a Linear Predictor. Lecture Notes In Computer Science 2010, 13: 502-509. PMID: 20879268, PMCID: PMC3889143, DOI: 10.1007/978-3-642-15705-9_61.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsComputer SimulationDogsEchocardiography, Three-DimensionalImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalLinear ModelsModels, CardiovascularMyocardial InfarctionPattern Recognition, AutomatedRadio WavesReproducibility of ResultsSensitivity and SpecificityConceptsLeft ventricular endocardial boundaryStandard level setSpatio-temporal coherenceCardiac segmentationBoundary detectionImage inhomogeneityEndocardial boundarySegmentationGeometric constraintsManual tracingRadio frequency ultrasoundLinear predictorLevel setsRF dataEchocardiographic imagesB-mode dataTrackingImagesDataConstraintsSetDetectionEstimation of 3D Geometry of Microtubules Using Multi-angle Total Internal Reflection Fluorescence Microscopy
Yang Q, Karpikov A, Toomre D, Duncan J. Estimation of 3D Geometry of Microtubules Using Multi-angle Total Internal Reflection Fluorescence Microscopy. Lecture Notes In Computer Science 2010, 13: 538-545. PMID: 20879357, DOI: 10.1007/978-3-642-15745-5_66.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalMicroscopy, FluorescenceMicrotubulesPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificityConceptsTotal internal reflection fluorescence microscopyReflection fluorescence microscopyTotal internal reflection fluorescence microscopy imagesPtK2 cellsMicrotubulesFluorescence microscopyTIRF imagesImportant biological parametersTIRF dataFluorescence microscopy imagesMulti-angle total internal reflection fluorescence microscopyBiological parametersMicrotubule curvatureBiological samplesTracking Clathrin Coated Pits with a Multiple Hypothesis Based Method
Liang L, Shen H, De Camilli P, Duncan JS. Tracking Clathrin Coated Pits with a Multiple Hypothesis Based Method. Lecture Notes In Computer Science 2010, 13: 315-322. PMID: 20879330, PMCID: PMC3889144, DOI: 10.1007/978-3-642-15745-5_39.Peer-Reviewed Original Research
2009
2D‐3D registration for prostate radiation therapy based on a statistical model of transmission images
Munbodh R, Tagare HD, Chen Z, Jaffray DA, Moseley DJ, Knisely JP, Duncan JS. 2D‐3D registration for prostate radiation therapy based on a statistical model of transmission images. Medical Physics 2009, 36: 4555-4568. PMID: 19928087, DOI: 10.1118/1.3213531.Peer-Reviewed Original ResearchAlgorithmsData Interpretation, StatisticalHumansImage Interpretation, Computer-AssistedImaging, Three-DimensionalInformation Storage and RetrievalMalePattern Recognition, AutomatedPhantoms, ImagingProstatic NeoplasmsRadiographic Image EnhancementRadiotherapy, ConformalReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueA dynamical shape prior for LV segmentation from RT3D echocardiography.
Zhu Y, Papademetris X, Sinusas AJ, Duncan JS. A dynamical shape prior for LV segmentation from RT3D echocardiography. 2009, 12: 206-13. PMID: 20425989, PMCID: PMC7814293.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceComputer SimulationComputer SystemsEchocardiography, Three-DimensionalHeart VentriclesHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalModels, AnatomicPattern Recognition, AutomatedPhantoms, ImagingReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueConceptsSubject-specific dynamical modelCurrent frameMotion patternsRecursive Bayesian frameworkSegmentation taskPast framesAutomatic segmentationPrevious frameSegmentation processLV segmentationManual segmentationSegmentationIntensity informationCardiac sequenceEchocardiographic sequencesStatic modelPrior knowledgeTemporal coherenceCardiac motionCardiac modelsBayesian frameworkGeneric dynamical modelEchocardiographic imagesFrameInter-subject variability
2008
Motion tracking of the outer tips of microtubules
Hadjidemetriou S, Toomre D, Duncan J. Motion tracking of the outer tips of microtubules. Medical Image Analysis 2008, 12: 689-702. PMID: 18571462, DOI: 10.1016/j.media.2008.04.004.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsArtificial IntelligenceHumansImage EnhancementImage Interpretation, Computer-AssistedMicroscopy, FluorescenceMicrotubulesMotionMovementPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificityConceptsMicrotubule assemblyCoordination of mitosisTransport of chromosomesHigh throughput quantitative studiesNumerous critical rolesMicrotubule tipsLiving cellsCell migrationStructural tracksConfocal microscopyEpifluorescent microscopyNeurodegenerative diseasesCritical roleCell pathologyMicrotubulesAssemblyCellsSequenceOuter tipChromosomesOrganellesMitosisAbnormal functionCytoplasmVesicles