2023
Super-resolution in brain positron emission tomography using a real-time motion capture system
Chemli Y, Tétrault M, Marin T, Normandin M, Bloch I, El Fakhri G, Ouyang J, Petibon Y. Super-resolution in brain positron emission tomography using a real-time motion capture system. NeuroImage 2023, 272: 120056. PMID: 36977452, PMCID: PMC10122782, DOI: 10.1016/j.neuroimage.2023.120056.Peer-Reviewed Original ResearchConceptsBrain positron emission tomographySuper-resolutionEvent-by-event basisReal-time motion capture systemSR reconstruction methodTracking cameraVisualization of small structuresPET reconstruction algorithmMoving phantomMeasure target motionLine profilesPET/CT scannerMeasured shiftsImprove image resolutionMotion capture systemMotion tracking devicePositron emission tomographyReconstruction algorithmSpatial resolutionMeasured linesPhantomReal-timeEstimation frameworkIncreased spatial resolutionReconstruction method
2022
Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling
Djebra Y, Marin T, Han P, Bloch I, Fakhri G, Ma C. Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling. IEEE Transactions On Medical Imaging 2022, 42: 158-169. PMID: 36121938, PMCID: PMC10024645, DOI: 10.1109/tmi.2022.3207774.Peer-Reviewed Original ResearchConceptsSpace alignmentSampled k-space dataState-of-the-art methodsIntrinsic low-dimensional manifold structureNumerical simulation studyLow-dimensional manifold structureState-of-the-artLinear subspace modelSparsity modelModel-based frameworkSubspace modelManifold structureMathematical modelManifold modelSparse samplingImage reconstructionMRI applicationsDynamic magnetic resonance imagingSpatiotemporal signalsSpatial resolutionPerformanceSimulation studyImagesMethodSparsityJoint spectral quantification of MR spectroscopic imaging using linear tangent space alignment‐based manifold learning
Ma C, Han P, Zhuo Y, Djebra Y, Marin T, Fakhri G. Joint spectral quantification of MR spectroscopic imaging using linear tangent space alignment‐based manifold learning. Magnetic Resonance In Medicine 2022, 89: 1297-1313. PMID: 36404676, PMCID: PMC9892363, DOI: 10.1002/mrm.29526.Peer-Reviewed Original ResearchConceptsSubspace-based methodsManifold learningIntrinsic low-dimensional structureGlobal coordinationLearning-based methodsNumerical simulation dataSpatial smoothness constraintSparsity constraintSpace alignmentSubspace modelSmoothness constraintSuperior performanceRoot mean square errorLinear transformationMechanical simulationsLow-dimensionalSquare errorSubspaceExperimental dataSpectroscopic imagingQuantum mechanical simulationsCoordinate alignmentMR spectroscopic imagingSpectral quantificationSimulated data
2019
Free-Breathing Three-Dimensional T1 Mapping of the Heart Using Subspace-Based Data Acquisition and Image Reconstruction
Han P, Horng D, Marin T, Petibon Y, Ouyang J, Fakhri G, Ma C. Free-Breathing Three-Dimensional T1 Mapping of the Heart Using Subspace-Based Data Acquisition and Image Reconstruction. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2019, 00: 4008-4011. PMID: 31946750, DOI: 10.1109/embc.2019.8856511.Peer-Reviewed Original ResearchConceptsRespiratory motionRespiratory gatingLongitudinal relaxation timeSubspace-based methodsLow-rank tensorMagnetic resonance imagingRelaxation timeT1 mappingT)-spaceSubspace-basedSparsity constraintDynamic MR imagingReconstructed mapsSpatiotemporal correlationThree-dimensionalCardiac MRHealthy subjectsIn vivo dataMagnetizationResonance imagingImage functionMR imagingData acquisitionClinical applicationTensor
2013
Numerical Surrogates for Human Observers in Myocardial Motion Evaluation From SPECT Images
Marin T, Kalayeh M, Parages F, Brankov J. Numerical Surrogates for Human Observers in Myocardial Motion Evaluation From SPECT Images. IEEE Transactions On Medical Imaging 2013, 33: 38-47. PMID: 23981533, PMCID: PMC4148467, DOI: 10.1109/tmi.2013.2279517.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBiomimeticsCoronary Artery DiseaseExpert SystemsHumansImage EnhancementImage Interpretation, Computer-AssistedMotionMyocardial Perfusion ImagingObserver VariationReproducibility of ResultsSensitivity and SpecificitySupport Vector MachineTomography, Emission-Computed, Single-PhotonConceptsHuman observer performanceRelevance vector machinePredicting human observer performanceDeformable mesh modelHuman observersHuman observer scoresImage-quality assessmentPerfusion-defect detectionMotion estimationModel observerMotion featuresVector machineMedical imagesLinear discriminantDefect detectionDetection taskMesh modelObserver performanceDiagnostic tasksNumerical surrogateTask-based approachApproximate surrogateTaskMotion evaluationPerformance
2010
Deformable left‐ventricle mesh model for motion‐compensated filtering in cardiac gated SPECT
Marin T, Brankov J. Deformable left‐ventricle mesh model for motion‐compensated filtering in cardiac gated SPECT. Medical Physics 2010, 37: 5471-5481. PMID: 21089783, PMCID: PMC2962663, DOI: 10.1118/1.3483098.Peer-Reviewed Original ResearchConceptsCardiac gated SPECTMesh modelNoise reductionMotion-compensated filteringCardiac gated SPECT imagingDeformable mesh modelTested clinical dataSignal-to-noise ratioMotion estimationMotion blurring artifactsEstimated motionImage-reconstruction methodsProcessing algorithmsSpatiotemporal filtering methodSpatiotemporal filteringMotion trajectoryFiltering approachMyocardium motionFiltering methodReduce noiseImage qualityTemporal correlationProcessing techniquesNoisePhoton data
2009
A quantitative evaluation study of four-dimensional gated cardiac SPECT reconstruction
Jin M, Yang Y, Niu X, Marin T, Brankov J, Feng B, Pretorius P, King M, Wernick M. A quantitative evaluation study of four-dimensional gated cardiac SPECT reconstruction. Physics In Medicine And Biology 2009, 54: 5643-5659. PMID: 19724094, PMCID: PMC3690946, DOI: 10.1088/0031-9155/54/18/019.Peer-Reviewed Original ResearchConceptsGated cardiac SPECT imagesNURBS-based cardiac-torso (NCATMotion-compensated temporal regularizationCardiac SPECT imagingBias-variance analysisDistance-dependent blurringGated cardiac SPECTMotion compensation approachReconstructed myocardiumSPECT imagesDetection of perfusion defectsSPECT reconstructionCardiac SPECTIntensity uniformityTemporal smoothnessPatient dataLeft ventricular myocardiumReconstructed imagesReconstruction processSpatial smoothingPerfusion defectsScatteringDegradation factorsTemporal regularityVentricular myocardiumMotion-compensated temporal summation of cardiac gated SPECT images using a deformable mesh model
Marin T, Wernick M, Yang Y, Brankov J. Motion-compensated temporal summation of cardiac gated SPECT images using a deformable mesh model. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2009, 2009: 3657-3660. PMID: 19964313, PMCID: PMC2810283, DOI: 10.1109/iembs.2009.5333693.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsCardiac-Gated Imaging TechniquesCardiac-Gated Single-Photon Emission Computer-Assisted TomographyComputer SimulationHeartHumansImage Processing, Computer-AssistedImaging, Three-DimensionalModels, StatisticalMotionPhantoms, ImagingRadiographic Image Interpretation, Computer-AssistedTomography, Emission-Computed, Single-PhotonConceptsDeformable mesh modelMotion blurring artifactsMesh modelCardiac gated SPECT imagingCardiac gated SPECTEstimating heart motionHeart motionNoisy imagesMotion estimationNoise reduction performanceTime dimensionEstimated motionBlurring artifactsIndividual framesPartial volume effectsNoise reductionQuantitative evaluationReduction performanceImagesNoiseSPECT imagesStatic SPECT imagesArtifactsFrameGate sequences