Thibault Marin, PhD
Assistant Professor of Radiology and Biomedical ImagingCards
About
Research
Publications
2026
Characterization and Initial Optimization of Reconstruction Performance for Detector Crosstalk of Ultra-high Performance Brain PET Imager
Zhang J, Fontaine K, Li T, Gravel P, Toyonaga T, Hu Y, Gallezot J, Zeng T, Volpi T, Lu Y, Marin T, Qi J, Carson R. Characterization and Initial Optimization of Reconstruction Performance for Detector Crosstalk of Ultra-high Performance Brain PET Imager. IEEE Transactions On Radiation And Plasma Medical Sciences 2026, PP: 1-1. DOI: 10.1109/trpms.2026.3698769.Peer-Reviewed Original ResearchDepth of interactionDetector crosstalkSpatial resolutionHigh-resolution PET systemsCompton scatteringScintillation crystalsPET systemBrain phantomCrystal elementsPoint spread functionHigh-sensitivity requirementsOptical isolatorMeasured energyInteraction pointBrain PET imagingPET/CT systemReal phantomReconstruction performancePartial volume effectsImage contrastHigh image contrastSpread functionPhantomResolution characterizationCrosstalk eventsPET Imaging in Head and Neck Squamous Cell Carcinoma: from Staging to Response Assessment
Beddok A, Prendergast C, Seban R, Safri S, Valika T, Ammari S, Bidault F, Sun R, Rozenblum L, Liao M, McGale J, Marin T, Tordjman M, Nguyen P, Naim A, Schwartz L, De Jong D, Papathanassiou D, Dercle L. PET Imaging in Head and Neck Squamous Cell Carcinoma: from Staging to Response Assessment. Current Oncology Reports 2026, 28: 13. PMID: 41661435, DOI: 10.1007/s11912-026-01745-y.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsHead and neck squamous cell carcinomaManagement of head and neck squamous cell carcinomaNeck squamous cell carcinomaSquamous cell carcinomaCell carcinomaPET imagingPositron Emission Tomography/Computed TomographyIndividualized radiotherapy plansMetabolic tumor volumeTotal lesion glycolysisEmission Tomography/Computed TomographyPersonalized managementPost-treatment settingCancer-associated fibroblastsLesion glycolysisNeck dissectionTomography/Computed TomographyTarget delineationDistant metastasisRadiotherapy planningTumor volumeAdvanced-stagePrognostic valueResponse assessmentAnatomic extentFree‐Running Three‐Dimensional Cardiac Extracellular Volume Mapping in a Single Scan With Mid‐Scan Contrast Injection
Lee W, Han P, Marin T, Mounime I, Chi D, Bijari F, Normandin M, Fakhri G, Ma C. Free‐Running Three‐Dimensional Cardiac Extracellular Volume Mapping in a Single Scan With Mid‐Scan Contrast Injection. Magnetic Resonance In Medicine 2026, 95: 3360-3368. PMID: 41656589, PMCID: PMC13049254, DOI: 10.1002/mrm.70293.Peer-Reviewed Original ResearchSignal modelContrast injectionECV mapsMR signal modelCine imagesThree-dimensionalK-space dataInversion recoveryExtracellular volume mappingSpace alignmentContrast agent injectionCardiac MR imagesEjection fractionIn vivo studiesCardiac cine imagingEstimated ejection fractionHealthy subjectsHematocrit levelsAgent injectionMR imagingBlood samplesHeart motionGradient echo readout
2025
Physics-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.ChaptersRobust 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 frameworkLR-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, 10: 535-546. PMID: 41424471, PMCID: PMC12714321, DOI: 10.1109/trpms.2025.3619872.Peer-Reviewed Original ResearchThis study introduces YRT-PET, an open-source GPU-accelerated software for PET image reconstruction, demonstrating high flexibility, speed, and compatibility with existing tools for dynamic imaging and motion correction.Predicting 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 parameters
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