Yanis Djebra, PhD
Postdoctoral AssociateAbout
Research
Publications
2024
Diffusion Model-Based Posterior Distribution Prediction for Kinetic Parameter Estimation in Dynamic PET
Djebra Y, Liu X, Marin T, Tiss A, Dhaynaut M, Guehl N, Johnson K, Fakhri G, Ma C, Ouyang J. Diffusion Model-Based Posterior Distribution Prediction for Kinetic Parameter Estimation in Dynamic PET. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635805.Peer-Reviewed Original ResearchPosterior distributions of kinetic parametersDenoising diffusion probabilistic modelHyperphosphorylated tauP-tauDiffusion probabilistic modelAlzheimer's diseaseNeurodegenerative diseasesKinetic parametersPosterior distributionInference efficiencyComputational needsEstimate kinetic parametersProbabilistic modelComputation timeSparsity Constrained Linear Tangent Space Alignment Model (LTSA) for 3d Cardiac Extracellular Volume Mapping
Mounime I, Lee W, Marin T, Han P, Djebra Y, Eslahi S, Gori P, Angelini E, Fakhri G, Ma C. Sparsity Constrained Linear Tangent Space Alignment Model (LTSA) for 3d Cardiac Extracellular Volume Mapping. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635692.Peer-Reviewed Original ResearchT)-space dataExtracellular volume mappingIntrinsic low-dimensional manifold structureCardiac tissue propertiesImproved image reconstructionLow-dimensional manifold structureExtracellular volumeFast MRI methodSparsity constraintModel-based methodsSuperior performanceSpace alignmentT1 mappingManifold structureImage reconstructionT)-spacePost-contrast T1 mappingTissue propertiesFree breathingConcentration of contrast agentLongitudinal relaxation timeAlignment modelDynamic MR imagingSparsityAlignment matrix
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 dataFree-running Simultaneous 3D Cardiac T1 Mapping and Cine Imaging Using a Linear Tangent Space Alignment Model
Djebra Y, Marin T, Han P, Bloch I, Fakhri G, Ma C. Free-running Simultaneous 3D Cardiac T1 Mapping and Cine Imaging Using a Linear Tangent Space Alignment Model. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2022 DOI: 10.58530/2022/4440.Peer-Reviewed Original Research
2021
Free‐breathing 3D cardiac T1 mapping with transmit B1 correction at 3T
Han P, Marin T, Djebra Y, Landes V, Zhuo Y, Fakhri G, Ma C. Free‐breathing 3D cardiac T1 mapping with transmit B1 correction at 3T. Magnetic Resonance In Medicine 2021, 87: 1832-1845. PMID: 34812547, PMCID: PMC8810588, DOI: 10.1002/mrm.29097.Peer-Reviewed Original ResearchConceptsFlip-angle estimationCardiac T<sub>1</sub> mappingGradient echo readoutThrough-plane spatial resolutionImaging timePractical imaging timesFree breathingPhantom studyB1 correctionAccelerated imagingIn-planeT)-spaceMyocardial T<sub>1</sub> valuesSubspace-based methodsSpatial resolutionImaging experimentsAcquisition schemeT)-space dataSubject-specific timeCorrectionModified Look-Locker inversion recoveryLook-Locker inversion recoveryTime of data acquisitionAverage imaging timeInversion-recovery sequence
2020
Motion correction for PET data using subspace-based real-time MR imaging in simultaneous PET/MR
Marin T, Djebra Y, Han P, Chemli Y, Bloch I, Fakhri G, Ouyang J, Petibon Y, Ma C. Motion correction for PET data using subspace-based real-time MR imaging in simultaneous PET/MR. Physics In Medicine And Biology 2020, 65: 235022. PMID: 33263317, PMCID: PMC7985095, DOI: 10.1088/1361-6560/abb31d.Peer-Reviewed Original ResearchConceptsPositron emission tomography reconstructionMotion-corrected PET reconstructionsPET reconstructionMotion-corrected PET imagesIrregular respiratory motionMotion fieldMotion correction methodMotion correction approachIrregular motion patternsUndersampled k-space dataImage quality of positron emission tomographyQuality of positron emission tomographyMotion patternsLow-rank characteristicsRespiratory motionContrast-to-noise ratioEstimated motion fieldSurrogate signalsMotion correctionK-space dataImage qualityReal-time MR imagingSimultaneous PET/MRMotion artifact reductionPET/MR scanners