2021
Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling
Zhuang J, Dvornek N, Tatikonda S, Papademetris X, Ventola P, Duncan J. Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling. Lecture Notes In Computer Science 2021, 12729: 58-70. DOI: 10.1007/978-3-030-78191-0_5.Peer-Reviewed Original ResearchOrdinary differential equationsAdjoint methodNoisy observationsMultiple shooting methodNon-linear systemsLarge scale continuous systemsLarge-scale systemsParameter value estimationDifferential equationsAccurate gradient estimationExpectation-maximization algorithmNon-linear modelParameter estimationBayesian frameworkGradient estimationContinuous systemToy exampleLarge systemsReal fMRI dataEstimationValue estimationAlgorithmGood accuracyCausal modelingModel changes
2017
The Generalized Steiner Cable-Trench Problem with Application to Error Correction in Vascular Image Analysis
Landquist E, Vasko F, Kresge G, Tal A, Jiang Y, Papademetris X. The Generalized Steiner Cable-Trench Problem with Application to Error Correction in Vascular Image Analysis. Operations Research Proceedings 2017, 391-397. DOI: 10.1007/978-3-319-55702-1_52.Peer-Reviewed Original Research
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
2010
A VTK-based, CUDA-optimized Non-Parametric Vessel Detection Method
Alpoge L, Joshi A, Scheinost D, Onofrey J, Qian X, Papademetris X. A VTK-based, CUDA-optimized Non-Parametric Vessel Detection Method. The VTK Journal 2010 DOI: 10.54294/z1w0uu.Chapters
2009
Unified framework for development, deployment and testing of image analysis algorithms
Joshi A, Scheinost D, Okuda H, Murphy I, Staib L, Papademetris X. Unified framework for development, deployment and testing of image analysis algorithms. The MIDAS Journal 2009 DOI: 10.54294/pq6gf6.Peer-Reviewed Original ResearchImage analysis algorithmsUser interface controlsUser interfaceAnalysis algorithmCommand-line user interfaceGraphical user interface controlsPlatform interoperabilityInterface controlSource codeComplex algorithmsSuch algorithmsNovel frameworkFramework idealMultiple platformsUnified frameworkAlgorithmRapid developmentDeploymentCustom pipelineImage analysisUsersPublic useFrameworkInteroperabilityDevelopers
2007
Local Shape Registration Using Boundary-Constrained Match of Skeletons
Zhu Y, Papademetris X, Sinusas A, Duncan J. Local Shape Registration Using Boundary-Constrained Match of Skeletons. 2007, 1-8. DOI: 10.1109/cvpr.2007.383427.Peer-Reviewed Original ResearchTarget objectDynamic pruning algorithmLocal shapePruning algorithmShape registration algorithmRegistration algorithmObject skeletonShape registrationCardiac sequenceAlgorithmShape correspondenceConstraint termBinary shapesMeaningful correspondenceBulky objectsLocal shape registrationPotential fieldObjects
2004
Construction of a 3D Volumetric Probabilistic Model of the Mouse Kidney from MRI
Okuda H, Shkarin P, Behar K, Duncan J, Papademetris X. Construction of a 3D Volumetric Probabilistic Model of the Mouse Kidney from MRI. Lecture Notes In Computer Science 2004, 3217: 1052-1054. DOI: 10.1007/978-3-540-30136-3_134.Peer-Reviewed Original ResearchProbabilistic volumetric modelVolumetric modelPoint matching algorithmRobust point matching algorithmLocal B-splineKidney segmentationGlobal linear transformationsSegmentation algorithmMatching algorithmFree-form deformationRegistration stepVolumetric imagesKidney imagesShape modelingProbabilistic modelForm deformationAlgorithmImagesB-splinesSegmentationUltimate goal
2003
Computing 3D Non-rigid Brain Registration Using Extended Robust Point Matching for Composite Multisubject fMRI Analysis
Papademetris X, Jackowski A, Schultz R, Staib L, Duncan J. Computing 3D Non-rigid Brain Registration Using Extended Robust Point Matching for Composite Multisubject fMRI Analysis. Lecture Notes In Computer Science 2003, 2879: 788-795. DOI: 10.1007/978-3-540-39903-2_96.Peer-Reviewed Original ResearchRobust Point MatchingIntensity-based registrationLarge point setsPoint matchingGreater computational efficiencyComputational efficiencyRobust pointSuperior performancePoint setsMagnetic resonance imagesBrain registrationActivation mapsFunctional magnetic resonance imagesSuccessful applicationRegistrationResonance imagesAlgorithmMatchingSpecificationMethodologyImagesRobustnessFrameworkSpecific areasSetAnalysis of Left Ventricular Motion Using a General Robust Point Matching Algorithm
Lin N, Papademetris X, Sinusas A, Duncan J. Analysis of Left Ventricular Motion Using a General Robust Point Matching Algorithm. Lecture Notes In Computer Science 2003, 2878: 556-563. DOI: 10.1007/978-3-540-39899-8_69.Peer-Reviewed Original ResearchPoint matching algorithmRobust point matching algorithmMatching algorithmNon-rigid cardiac motionDimensional medical imagesShape-based informationRobust Point MatchingCardiac magnetic resonance imagesNon-rigid transformationMedical imagesNumber of applicationsPoint matchingSynthetic dataAlgorithmOwn previous workLeft ventricular motionMagnetic resonance imagesCardiac motionImagesPrevious workResonance imagesSegmentationMatchingVentricular motionPriors
1996
Estimation of motion boundary location and optical flow using dynamic programming
Papademetris X, Belhumeur P. Estimation of motion boundary location and optical flow using dynamic programming. 1996, 1: 509-512 vol.1. DOI: 10.1109/icip.1996.559545.Peer-Reviewed Original Research