Thibault Marin, PhD
Assistant Professor of Radiology and Biomedical ImagingCards
About
Research
Publications
2025
Impact of Depth-of-Interaction and Spatially-Variant Point-Spread-Function Model on the Performance of Ultra-High Resolution Brain PET
Zeng T, Najmaoui Y, Zhang J, Fontaine K, Hu Y, Chemli Y, Gallezot J, Sun C, Lu Y, Fakhri G, Carson R, Marin T. Impact of Depth-of-Interaction and Spatially-Variant Point-Spread-Function Model on the Performance of Ultra-High Resolution Brain PET. 2021 IEEE Nuclear Science Symposium And Medical Imaging Conference (NSS/MIC) 2025, 1-2. DOI: 10.1109/nss/mic/rtsd57106.2025.11287015.Peer-Reviewed Original ResearchSpatially-varying point spread functionPoint spread functionAccurate point spread functionPSF modelConvergence behaviorImage qualityPoint spread function modelReconstruction toolboxPSF parametersHigh-activity regionsBrain-dedicated PET scannersDepth of interactionPoint-spread-function modelingField of viewSpatial resolutionHuman scansContrast recoverySpread functionPET systemPET scannerReal phantomBrain phantomMonte Carlo simulationsBrain positron emission tomographyCarlo simulationsPhysics-Informed List-Mode Deep Image Prior Reconstruction with Motion Correction in 3D Brain PET
Chemli Y, Najmaoui Y, Normandin M, Fakhri G, Marin T, Ouyang J. Physics-Informed List-Mode Deep Image Prior Reconstruction with Motion Correction in 3D Brain PET. 2021 IEEE Nuclear Science Symposium And Medical Imaging Conference (NSS/MIC) 2025, 1-2. DOI: 10.1109/nss/mic/rtsd57106.2025.11287851.Peer-Reviewed Original ResearchDeep Image PriorList-modeContrast recoveryMotion correctionList-mode eventsReconstructed activity distributionHoffman brain phantomNoise-resolution trade-offML-EM reconstructionLow-count dataResolution phantomBrain phantomBrain positron emission tomographySuper-resolution effectActivity distributionModel attenuationML-EMBack-projection operationsFine structureDown-sampled dataNegative log-likelihoodImage registrationUnsupervised regularizerBack-projectionImage priorsMulticenter PET Image Harmonization Using Style-Guided CycleGAN in Primary Central Nervous System Lymphoma : InStyleGAN
Arzur D, Marin T, Horowitz T, Kas A, El Fakhri G, Mhiri I, Rozenblum L. Multicenter PET Image Harmonization Using Style-Guided CycleGAN in Primary Central Nervous System Lymphoma : InStyleGAN. Lecture Notes In Computer Science 2025, 16164: 126-138. DOI: 10.1007/978-3-032-07904-6_12.Peer-Reviewed Original ResearchRobust deep learning modelAdaptive instance normalizationTarget modalityDeep learning modelsInstance NormalizationDistribution alignmentDomain shiftImage harmonizationModel generalizationLatent domainsLearning modelsComputational costNon-scalableCycleGANImage dataData pairsPrimary central nervous system lymphomaAcquisition settingsFrameworkCentral nervous system lymphomaPET dataDomainDataNervous system lymphomaHarmonized frameworkYRT-PET-NX: Development of a Plugin for an Open-Source PET Reconstruction Platform to Support the NeuroEXPLORER
Najmaoui Y, Fontaine K, Fontaine D, Zhang J, Zeng T, Volpi T, Chemli Y, Gallezot J, Tétrault M, Carson R, Fakhri G, Marin T. YRT-PET-NX: Development of a Plugin for an Open-Source PET Reconstruction Platform to Support the NeuroEXPLORER. 2025, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57106.2025.11287275.Peer-Reviewed Original ResearchOpen-sourcePeak-to-valley ratioMini-Derenzo phantomReconstruction platformResolution PET scannerImage reconstruction toolsPacket decodingDetector geometryGPU accelerationMemory usagePET scannerPET systemAccurate system modelMotion correctionScatter estimationVendor softwareReconstruction timeImage reconstructionPluginImage qualitySoftwareHuman datasetsSystem modelManufacturing softwareNon-human primatesLR-PET: A Subspace-Based Dynamic PET Imaging via Explicit Non-Negative Low-Rank Factorization
Djebra Y, Najmaoui Y, Chemli Y, Normandin M, Fakhri G, Ma C, Marin T. LR-PET: A Subspace-Based Dynamic PET Imaging via Explicit Non-Negative Low-Rank Factorization. 2025, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57106.2025.11286709.Peer-Reviewed Original ResearchYRT-PET: An Open-Source GPU-Accelerated Image Reconstruction Engine for Positron Emission Tomography
Najmaoui Y, Chemli Y, Toussaint M, Petibon Y, Marty B, Fontaine K, Gallezot J, Razdevsek G, Orehar M, Dhaynaut M, Guehl N, Dolenec R, Pestotnik R, Johnson K, Ouyang J, Normandin M, Tetrault M, Lecomte R, Fakhri G, Marin T. YRT-PET: An Open-Source GPU-Accelerated Image Reconstruction Engine for Positron Emission Tomography. IEEE Transactions On Radiation And Plasma Medical Sciences 2025, PP: 1-1. PMID: 41424471, PMCID: PMC12714321, DOI: 10.1109/trpms.2025.3619872.Peer-Reviewed Original ResearchOpen-sourceImage reconstructionPositron emission tomography image reconstructionReconstruction algorithmAdvanced image reconstruction algorithmsOpen-source toolkitDevelopment of advanced algorithmsTime-of-flightScanner geometryNovel reconstruction algorithmImage reconstruction algorithmMotion correctionReusable codeGPU accelerationTime-of-flight informationPython bindingsPlugin systemSoftware toolkitMeaningful imagesData formatsFast implementationRigid motion correctionAdvanced algorithmsPoint spread function modelProprietary softwarePredicting tumor recurrence site after reirradiation in head and neck cancer: a retrospective external validation of a published [18F]-FDG PET radiomic signature
Beddok A, Grogg K, Nioche C, Rozenblum L, Orlhac F, Calugaru V, Crehange G, Shih H, Marin T, Buvat I, El Fakhri G. Predicting tumor recurrence site after reirradiation in head and neck cancer: a retrospective external validation of a published [18F]-FDG PET radiomic signature. La Radiologia Medica 2025, 130: 1854-1863. PMID: 40833475, DOI: 10.1007/s11547-025-02072-1.Peer-Reviewed Original ResearchHead and neck cancerPET radiomics signaturePositive predictive valueNeck cancerRadiomics signatureRecurrent head and neck cancerExternal cohortTumor recurrence siteDose escalationLocoregional failurePET radiomicsRecurrence siteMassachusetts General HospitalLIFEx softwareIndependent cohortRadiomic featuresOriginal cutoffPatientsPredictive valuePublished cutoffsPurposeThis studyCohortGeneral HospitalRecurrenceConclusionThe studyIn vivo 3D myocardial membrane potential mapping in humans using PET/MRI
Bijari F, Han P, Marin T, Lee W, Chemli Y, Gertsenshteyn I, Mounime I, Djebra Y, Chi D, Normandin M, Ma C, Fakhri G. In vivo 3D myocardial membrane potential mapping in humans using PET/MRI. EJNMMI Research 2025, 15: 93. PMID: 40715686, PMCID: PMC12297085, DOI: 10.1186/s13550-025-01287-7.Peer-Reviewed Original ResearchMembrane potentialExtracellular volume fraction measurementsExtracellular volume fraction mappingBolus-plus-infusion protocolT1 mapping sequencesVolume of distributionWritten Informed ConsentCardiac PET/MR imagingRigid image registrationHumans in vivoContrast agent injectionPET motion correctionFree breathingTracer volume of distributionImage registrationBolus injectionCardiac MRMitochondrial membrane potentialCardiac diseaseHealthy subjectsPET/MR imagingImaging studiesTreatment monitoringAgent injectionPET tracersBayesian Posterior Distribution Estimation of Kinetic Parameters in Dynamic Brain PET Using Generative Deep Learning Models
Djebra Y, Liu X, Marin T, Tiss A, Dhaynaut M, Guehl N, Johnson K, Fakhri G, Ma C, Ouyang J. Bayesian Posterior Distribution Estimation of Kinetic Parameters in Dynamic Brain PET Using Generative Deep Learning Models. IEEE Transactions On Medical Imaging 2025, 44: 5089-5102. PMID: 40663684, PMCID: PMC12318411, DOI: 10.1109/tmi.2025.3588859.Peer-Reviewed Original ResearchPosterior distributions of kinetic parametersEfficiency of deep learningGenerative deep learning modelsConditional variational autoencoderDeep learning modelsComputational efficiencyMetropolis-Hastings MCMCPosterior distributionHyperphosphorylated tauDynamic brain positron emission tomographyWGAN-GPDual decodersWasserstein GANVariational autoencoderKinetic parametersDeep learningComputational needsBayesian inferenceP-tauLearning modelsAlzheimer's diseaseNeurodegenerative diseasesComputation timeMCMC methodsEstimation of kinetic parametersFast 3D cardiac extracellular volume mapping and cine imaging via continuous free-breathing acquisition with mid-scan contrast agent injection
Lee W, Han P, Marin T, Mounime I, Bijari F, Normandin M, Fakhri G, Ma C. Fast 3D cardiac extracellular volume mapping and cine imaging via continuous free-breathing acquisition with mid-scan contrast agent injection. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2025 DOI: 10.58530/2025/0789.Peer-Reviewed Original ResearchContrast agent injectionExtracellular volume mappingCine imagesContrast agent administrationExtracellular volumeFree-breathing scanFree-breathing acquisitionECV mapsAgent injectionAgent administrationTotal scan timeCardiac imaging methodsImage reconstructionScan timeCardiac motionSpace alignmentCineTime efficiency
News
News
- June 02, 2025
Zeng receives travel award for SNMMI
- March 05, 2025
PET mapping of receptor occupancy using joint direct parametric reconstruction
- February 03, 2025Source: Magnetic Resonance in Imaging
Free‐breathing 3D cardiac extracellular volume (ECV) mapping using a linear tangent space alignment (LTSA) model
- January 24, 2025
Welcome New Faculty, Fellows & Staff to Yale BIDS