2025
Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model
Dong Y, Marin T, Zhuo Y, Najem E, Beddok A, Rozenblum L, Moteabbed M, Grogg K, Xing F, Woo J, Chen Y, Lim R, Liu X, Ma C, Fakhri G. Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model. Medical Physics 2025 PMID: 40317577, DOI: 10.1002/mp.17865.Peer-Reviewed Original ResearchClinical target volumeGross tumor volumeClinical target volume delineationSoft tissue sarcomasInter-reader variabilityTissue sarcomasClinical target volume contoursMagnetic resonance imagingCTV delineationTarget volume delineationComputed tomographyTreatment of soft tissue sarcomasFluorodeoxyglucose positron emission tomographyCTV contoursTarget volumeVolume delineationT1-weighted magnetic resonance imagingRadiotherapy treatmentEnergy distanceHigh Dice indexPositron emission tomographyTumor volumeMicroscopic spreadFDG-PETTreatment planningDual Prompting for Diverse Count-Level Pet Denoising
Liu X, Huang Y, Marin T, Chemli Y, Eslahi S, Tiss A, Johnson K, Fakhri G, Ouyang J. Dual Prompting for Diverse Count-Level Pet Denoising. 2025, 00: 1-5. DOI: 10.1109/isbi60581.2025.10980695.Peer-Reviewed Original ResearchFlexible and modular PET: Evaluating the potential of TOF‐DOI panel detectors
Razdevšek G, Fakhri G, Marin T, Dolenec R, Orehar M, Chemli Y, Gola A, Gascon D, Majewski S, Pestotnik R. Flexible and modular PET: Evaluating the potential of TOF‐DOI panel detectors. Medical Physics 2025, 52: 2845-2860. PMID: 40089973, PMCID: PMC12059530, DOI: 10.1002/mp.17741.Peer-Reviewed Original ResearchDepth of interactionLong axial field-of-viewTime-of-flightPanel detectorHigh-performance computing clusterDepth-of-interaction resolutionNoise equivalent count rateDepth-of-interaction capabilityDepth-of-interaction detectorsAxial field-of-viewImage qualityTime-of-Flight (TOFDistortion-free imagesPositron emission tomography scannerLong axial fieldComputer clusterSpatial resolutionLSO crystalsImage reconstructionDetector materialCount rateGATE softwareContrast-to-noise ratioParallax errorMonte Carlo simulationsPET Mapping of Receptor Occupancy Using Joint Direct Parametric Reconstruction
Marin T, Belov V, Chemli Y, Ouyang J, Najmaoui Y, Fakhri G, Duvvuri S, Iredale P, Guehl N, Normandin M, Petibon Y. PET Mapping of Receptor Occupancy Using Joint Direct Parametric Reconstruction. IEEE Transactions On Biomedical Engineering 2025, 72: 1057-1066. PMID: 39446540, PMCID: PMC11875991, DOI: 10.1109/tbme.2024.3486191.Peer-Reviewed Original ResearchCentral nervous systemReceptor occupancyLow-binding regionsPET scansSimulation resultsPreclinical in vivo experimentsDynamic PET scansPairs of baselineEstimation of receptor occupancyEstimation frameworkPET neuroimagingReconstruction frameworkModulating drugsTime activity curvesParametric reconstructionDevelopment of drugsGross tumor volume confidence maps prediction for soft tissue sarcomas from multi-modality medical images using a diffusion model
Dong Y, Marin T, Zhuo Y, Najem E, Moteabbed M, Xing F, Beddok A, Lahoud R, Rozenblum L, Ding Z, Liu X, Grogg K, Woo J, Chen Y, Lim R, Ma C, Fakhri G. Gross tumor volume confidence maps prediction for soft tissue sarcomas from multi-modality medical images using a diffusion model. Physics And Imaging In Radiation Oncology 2025, 33: 100734. PMID: 40123775, PMCID: PMC11926426, DOI: 10.1016/j.phro.2025.100734.Peer-Reviewed Original ResearchGross tumor volumeSoft tissue sarcomasTissue sarcomasGross tumor volume delineationManual GTV delineationsMagnetic resonance imagingComputed tomographyFluorodeoxyglucose positron emission tomographyGTV delineationT1-weighted magnetic resonance imagingSingle-modePositron emission tomographyMulti-modal medical imagesTumor volumeIntra-reader variabilityFDG-PETTreatment planningSarcomaEmission tomographyImaging modalitiesResonance imagingDiffusion modelDice indexReader variabilityPatients
2024
Diffusion-based Bayesian posterior distribution prediction of kinetic parameters in dynamic PET
Djebra Y, Liu X, Marin T, Tiss A, Dhaynaut M, Guehl N, Johnson K, Fakhri G, Ma C, Ouyang J. Diffusion-based Bayesian posterior distribution prediction of kinetic parameters in dynamic PET. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10657955.Peer-Reviewed Original ResearchConditional variational autoencoderEfficient deep learning-based approachMarkov chain Monte CarloDenoising diffusion probabilistic modelDeep learning-based approachDiffusion probabilistic modelLearning-based approachApproximate posterior distributionPosterior distributionVariational autoencoderHeavy computationTau protein aggregationBayesian inferenceProbabilistic modelData-drivenStudy molecular processesBayesian posterior distributionProtein aggregationMetropolis-Hastings Markov chain Monte CarloMolecular processesAlzheimer's diseaseNeurodegenerative diseasesKinetic parametersEstimate posterior distributionsAutoencoderMultimodality Molecular Imaging of Brain Tumor Using Simultaneous [18F]FET-PET/MRSI
Ma C, Han P, Marin T, Zhuo Y, Shih H, Fakhri G. Multimodality Molecular Imaging of Brain Tumor Using Simultaneous [18F]FET-PET/MRSI. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10656528.Peer-Reviewed Original ResearchList-mode dataMR spectroscopic imagingSpatial resolutionAccurate brain tumor delineationMR physicsIsotropic resolutionBrain tumor delineationImprove treatment planningSpectroscopic imagingTumor delineationSignal-to-noise ratioIntact blood-brain barrierImaging speedAmino acid radiotracerImaging timeMR signalHigher proliferation activityStructural MRTreatment planningBlood-brain barrierMR spectroscopic imaging dataMolecular imaging of brain tumorsTumor involvementTumor infiltrationTumor marginsPET motion correction using subspace-based real-time MR imaging in simultaneous PET/MR
Mounime I, Marin T, Han P, Ouyang J, Gori P, Angelini E, Fakhri G, Ma C. PET motion correction using subspace-based real-time MR imaging in simultaneous PET/MR. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10657647.Peer-Reviewed Original ResearchOrdered-subset expectation maximizationMotion correctionGated reconstructionsMotion-corrected PET reconstructionsPET eventsCardiac motion phasesMotion correction methodCardiac motionMotion phaseReconstructed dynamic imagesPET reconstructionReal-time MR imagingSimultaneous PET/MRPatient motionSoft tissue contrastDynamic MR image reconstructionReference phaseMitigate artifactsLow-rank propertyMR image reconstructionPositron emission tomographyManifold learning frameworkSpatial resolutionBlurring artifactsImage reconstructionIntegration of a continuously varying image-space PSF for a dual-panel ultra-high TOF-PET scanner
Chemli Y, Marin T, Orehar M, Dolenec R, Normandin M, Gascón D, Gola A, Grogg K, Pavón G, Razdevsek G, Pestotnik R, Fakhri G. Integration of a continuously varying image-space PSF for a dual-panel ultra-high TOF-PET scanner. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10656225.Peer-Reviewed Original ResearchGaussian mixture modelGaussian process regressionPoint spread functionAccurate image reconstructionMaximum likelihood estimation maximizationShift-variant convolutionsImage reconstructionMixture modelProcess regressionEstimation maximizationTime-of-flight (TOFPanel architectureSpread functionArchitectureParameter interpolationHigh resolution time-of-flight (TOFTOF-PET scannerBrain phantomFitting processPositron emission tomography scannerSimulated point sourcesConvolutionAlgorithmEffective diagnosisSize benefitsFlat Panel TOF-PET Detectors: a Simulation Study
Orehar M, Dolenec R, Fakhri G, Gascón D, Gola A, Korpar S, Križan P, Razdevšek G, Marin T, Chemli Y, Žontar D, Pestotnik R. Flat Panel TOF-PET Detectors: a Simulation Study. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10658250.Peer-Reviewed Original ResearchTime resolutionAngular coverageFlat-panel detectorScintillation materialsGATE softwareAxial coverageBiograph VisionPanel detectorTotal-body coverageClinical scannerImage reconstructionDetectorReconstructed imagesHomogeneous contrastCylindrical scannerImage qualityState-of-the-artScintillationHigh-performance computingScannerPhantomResolutionCore hoursPositron emission tomographyGateRadiomics-driven personalized radiotherapy for primary and recurrent tumors: A general review with a focus on reirradiation
Beddok A, Orlhac F, Rozenblum L, Calugaru V, Créhange G, Dercle L, Nioche C, Thariat J, Marin T, El Fakhri G, Buvat I. Radiomics-driven personalized radiotherapy for primary and recurrent tumors: A general review with a focus on reirradiation. Cancer/Radiothérapie 2024, 28: 597-602. PMID: 39406602, DOI: 10.1016/j.canrad.2024.09.002.Peer-Reviewed Original ResearchPersonalized radiotherapyTumor localizationTreatment planningMedian AUCImaging modalitiesRisk of recurrenceHead and neckImprove treatment precisionPredicting clinical outcomesOptimal treatment planQuantitative imaging biomarkersRecurrent tumorsApplication of radiomicsRecurrent cancerClinical radiotherapyExternal validationClinical outcomesRadiotherapyReirradiationLack of external validationMEDLINE searchTreatment precisionImaging biomarkersImaging protocolTumorFree‐breathing 3D cardiac extracellular volume (ECV) mapping using a linear tangent space alignment (LTSA) model
Lee W, Han P, Marin T, Mounime I, Eslahi S, Djebra Y, Chi D, Bijari F, Normandin M, Fakhri G, Ma C. Free‐breathing 3D cardiac extracellular volume (ECV) mapping using a linear tangent space alignment (LTSA) model. Magnetic Resonance In Medicine 2024, 93: 536-549. PMID: 39402014, PMCID: PMC11606777, DOI: 10.1002/mrm.30284.Peer-Reviewed Original ResearchExtracellular volume mappingContrast agent injectionExtracellular volumeGradient echo readoutECV mapsAgent injectionWhole heartEcho readoutExtracellular volume valuesVoxel-by-voxelInversion recovery sequenceSpatial resolutionScan timeImaging timeIn vivo studiesHealthy volunteersModel-based methodsRecovery sequenceInjectionReadoutSubject-aware PET Denoising with Contrastive Adversarial Domain Generalization
Liu X, Marin T, Eslahi S, Tiss A, Chemli Y, Johson K, Fakhri G, Ouyang J. Subject-aware PET Denoising with Contrastive Adversarial Domain Generalization. 2011 IEEE Nuclear Science Symposium Conference Record 2024, 00: 1-1. PMID: 39445307, PMCID: PMC11497478, DOI: 10.1109/nss/mic/rtsd57108.2024.10656150.Peer-Reviewed Original ResearchDomain generalizationDenoising performanceDenoising moduleDeep learningSubject-independent mannerSubject-invariant featuresSuperior denoising performanceAdversarial learning frameworkSubject-related informationConventional UNetBottleneck featuresTrustworthy systemsLearning frameworkDL modelsDL model performanceDenoisingNoise realizationsNegative samplesList-mode dataImage volumesModel performancePerformancePerformance of positron emission tomographyUNetFraction of eventsDesign Optimisation of a Flat-Panel, Limited-Angle TOF-PET Scanner: A Simulation Study
Orehar M, Dolenec R, Fakhri G, Korpar S, Križan P, Razdevšek G, Marin T, Žontar D, Pestotnik R. Design Optimisation of a Flat-Panel, Limited-Angle TOF-PET Scanner: A Simulation Study. Diagnostics 2024, 14: 1976. PMID: 39272760, PMCID: PMC11487429, DOI: 10.3390/diagnostics14171976.Peer-Reviewed Original ResearchTime-of-flight positron emission tomographyTOF-PET scannerNEMA NU 2Evaluate spatial resolutionPET detectorsNU 2Scintillation materialsBiograph VisionRing scannerLimited-angleScanner designReadout levelsPoint sourcesFlat panel geometryClinical scannerSpatial resolutionReadout strategySingle-crystalImage qualityScintillationScannerFlat panelDesign parametersDetectorDesign optimisationEffects of List-Mode-Based Intraframe Motion Correction in Dynamic Brain PET Imaging
Tiss A, Chemli Y, Guehl N, Marin T, Johnson K, Fakhri G, Ouyang J. Effects of List-Mode-Based Intraframe Motion Correction in Dynamic Brain PET Imaging. IEEE Transactions On Radiation And Plasma Medical Sciences 2024, 8: 950-958. PMID: 39507127, PMCID: PMC11540417, DOI: 10.1109/trpms.2024.3432322.Peer-Reviewed Original ResearchSparsity 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 matrixFree-breathing 3D cardiac extracellular volume (ECV) mapping using a linear tangent space alignment (LTSA) model
Lee W, Han P, Marin T, Mounime I, Eslahi S, Djebra Y, Chi D, Fakhri G, Ma C. Free-breathing 3D cardiac extracellular volume (ECV) mapping using a linear tangent space alignment (LTSA) model. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2024 DOI: 10.58530/2024/1493.Peer-Reviewed Original ResearchA deep learning-based approach to nuisance signal removal from MRSI data aqcuired without suppression
Lee W, Zhuo Y, Marin T, Han P, Chi D, El Fakhri G, Ma C. A deep learning-based approach to nuisance signal removal from MRSI data aqcuired without suppression. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2024 DOI: 10.58530/2024/0259.Peer-Reviewed Original ResearchDeep learning-based methodsLearning-based methodsU-Net structureSignal removalIn vivo MRSI dataNeural networkU-NetMRSI dataImage reconstructionSuperior performanceData processingRobust performanceHankel matrixNetworkNuisance signalsConventional methodsPerformanceMRSI signalsSignalMethodRemove nuisance signalsRemovalHankelDiffusion 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. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2024, 00: 1-5. PMID: 39530051, PMCID: PMC11554386, 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 time593: Using [18F]-FDG PET Radiomics to Predict Survival After Reirradiation in Head and Neck Cancer
Beddok A, Grogg K, Rozenblum L, Nioche C, Orhlac F, Calugaru V, Crehange G, Shih H, Marin T, Fakhri G, Buvat I. 593: Using [18F]-FDG PET Radiomics to Predict Survival After Reirradiation in Head and Neck Cancer. Radiotherapy And Oncology 2024, 194: s1210-s1212. DOI: 10.1016/s0167-8140(24)01168-x.Peer-Reviewed Original Research
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