Georges El Fakhri, PhD, DABR
Elizabeth Mears and House Jameson Professor of Radiology and Biomedical Imaging, Therapeutic Radiology and of Biomedical Informatics & Data ScienceCards
About
Research
Publications
2026
Molecular Engineering of Antibody-based Positron Emission Tomography Tracers for Central Nervous System Targeting (P2-7.002)
Paez-Garcia S, Ricaurte-Fajardo A, El Fakhri G, Grogg K, Franceschi A. Molecular Engineering of Antibody-based Positron Emission Tomography Tracers for Central Nervous System Targeting (P2-7.002). Neurology 2026, 106 DOI: 10.1212/wnl.0000000000216372.Peer-Reviewed Original ResearchNext-generation Brain-dedicated PET Systems: From Detector Design to Translational Neuroscience (P5-7.001)
Paez-Garcia S, Ricaurte-Fajardo A, Grogg K, Franceschi A, El Fakhri G. Next-generation Brain-dedicated PET Systems: From Detector Design to Translational Neuroscience (P5-7.001). Neurology 2026, 106 DOI: 10.1212/wnl.0000000000216393.Peer-Reviewed Original ResearchInfluence of an AQP4 haplotype and sleep duration on early Alzheimer's disease
Palatsides E, Yiallourou S, Himali D, Cavuoto M, Baril A, Yang Q, Peloso G, Ryan J, Fakhri G, Ghosh S, Thibault E, DeCarli C, Johnson K, Beiser A, Seshadri S, Himali J, Pase M. Influence of an AQP4 haplotype and sleep duration on early Alzheimer's disease. Alzheimer's & Dementia 2026, 22: e71540. PMID: 42222915, PMCID: PMC13239115, DOI: 10.1002/alz.71540.Peer-Reviewed Original ResearchConceptsGenetic variationAD pathologyAlzheimer's diseaseTau burdenAssociated with AD pathologyFramingham Heart StudyAmyloid-bRegional tau burdenSleep durationTau accumulationAllele carriersDementia-free participantsTauAllelesAD biomarkersShort sleep durationAquaporin-4Heart StudyPositron emission tomographySelf-ReportHomozygotesShort sleepHaplotypesScan-wise generalized PET denoising with contrastive adversarial learning
Liu X, Marin T, Eslahi S, Tiss A, Chemli Y, Najmaoui Y, Jang S, Fakhri G, Ouyang J. Scan-wise generalized PET denoising with contrastive adversarial learning. Physics In Medicine And Biology 2026, 71: 105030. PMID: 42173146, PMCID: PMC13312193, DOI: 10.1088/1361-6560/ae7231.Peer-Reviewed Original ResearchConceptsAdversarial frameworkContrastive lossDomain generalizationCross-entropyPeak signal-to-noise ratioSuperior denoising performanceContrastive learning schemeStructural similarity indexNoise realizationsAdversarial learningAdversarial trainingDenoising performanceSignal-to-noise ratioLearning schemeNegative pairsDeep learningAdversarial methodsPositive pairsStandard baselinesMutual informationDenoisingPerformance degradationSimilarity indexDistribution shiftsDomain distributionDirect Cardiac T1 Mapping with Subspace Modeling and Free-breathing Data Acquisition
Marin T, Han P, Szezurek D, Zhuo Y, Mounime I, Djebra Y, Lee W, Fakhri G, Ma C. Direct Cardiac T1 Mapping with Subspace Modeling and Free-breathing Data Acquisition. IEEE Transactions On Biomedical Engineering 2026, PP: 1-10. PMID: 42184172, PMCID: PMC13249525, DOI: 10.1109/tbme.2026.3696845.Peer-Reviewed Original ResearchAlternating Direction Method of MultipliersAlternating Direction MethodSubspace modelTotal variationImage denoising problemLow-rank constraintEstimation frameworkImage reconstruction problemEnd-to-endMethod of MultipliersDenoising problemSparsity constraintData acquisitionReconstruction frameworkReconstruction problemImage reconstructionOptimization problemFree breathingNumerical simulationsSubspaceFree-breathing acquisitionRelaxation modelPhysical knowledgeFrameworkImagesIndividualized treatment effect inference of head and neck cancer with multimodal data
Wei Y, Li Z, Woo J, Ouyang J, Fakhri G, Liu X. Individualized treatment effect inference of head and neck cancer with multimodal data. APSIPA Transactions On Signal And Information Processing 2026, 15: 3-20. PMID: 42125301, PMCID: PMC13160251, DOI: 10.1108/atsip-06-2025-0051.Peer-Reviewed Original ResearchHead and neck cancerAdversarial trainingMultimodal patient dataDeep learningHead and neck cancer casesMultimodal dataRobust estimates of causal effectsEnd-to-end deep learningMutual informationPatient-specific outcomesSelection biasEstimation of causal effectsAdaptive instance normalizationPatient dataNeck cancerMultimodal medical imagesEnd-to-endIndividual treatment effects estimationStatus featuresRetrospective observational dataInstance NormalizationTreatment effectsInformation fusionPatient characteristicsMedical imagesUnsupervised Adaptation from FDG to PSMA PET/CT for 3D Lesion Detection Under Label Shift
Liu X, Xia M, Chemli Y, Fakhri G, Liu C, Ouyang J. Unsupervised Adaptation from FDG to PSMA PET/CT for 3D Lesion Detection Under Label Shift. 2026, 00: 1-5. DOI: 10.1109/isbi61048.2026.11515918.Peer-Reviewed Original ResearchUnsupervised domain adaptationLabel shiftPseudo-labelsSupervised learningSelf-trainingPseudo-label selectionBox regressionDomain adaptationUnsupervised adaptationCovariate shiftConfidence thresholdLesion detectionLearningLabelingDetectionAnchor shapeUnsupervisedFROCHistogramAdaptationSize compositionPseudoLatent diffusion transformers for 3D head and neck tumor segmentation
Dong Y, Marin T, Grogg K, Beddok A, Liu X, Moteabbed M, Woo J, Ma C, Fakhri G. Latent diffusion transformers for 3D head and neck tumor segmentation. Progress In Biomedical Optics And Imaging 2026, 13926: 31. DOI: 10.1117/12.3085831.Peer-Reviewed Original ResearchGross tumor volumeFowlkes–Mallows scoreExpressive powerAccurate segmentationComputed tomographyTumor segmentationFluorodeoxyglucose positron emission tomographyMedical image dataRadiotherapy planningGlobal spatial dependenciesLatent representationVision TransformerTransformer architectureComprehensive experimentsPositron emission tomographyH tumorsTumor volumeFDG-PETBoundary accuracyMask generationClinical decision-makingDice scoreVolumetric inputSuperior performanceEmission tomographyAI‑driven multi-lesion detection in whole‑body FDG PET/CT
Liu X, Xia M, Chemli Y, Fakhri G, Liu C, Ouyang J. AI‑driven multi-lesion detection in whole‑body FDG PET/CT. Progress In Biomedical Optics And Imaging 2026, 13928: 7. DOI: 10.1117/12.3087729.Peer-Reviewed Original ResearchWhole-body FDG PET/CTFDG-PET/CTLesion detectionFDG-PET/CT studiesIntersection-over-unionOncologic PET/CTLesion detection networkDetection of lesionsDeep learning modelsCT informationDiagnostic accuracyPET-onlyTreatment planningLesion sizePET/CTObject detectorsEfficiency of radiologistsIoU thresholdLesionsDetection modelPublic datasetsDetectorDetection networkNumerous lesionsLocalization performanceExploring the limits of deep-learning‑based PET image denoising for lesion detectability
Bayerlein R, Xia M, Ouyang J, Chemli Y, Melnichuk D, Fakhri G, Nardo L, Liu C, Badawi R. Exploring the limits of deep-learning‑based PET image denoising for lesion detectability. Progress In Biomedical Optics And Imaging 2026, 13928: 5. DOI: 10.1117/12.3085222.Peer-Reviewed Original ResearchDenoised imageDL-based denoisersLesion contrastDetectability of low-contrast lesionsDL-basedInformation diffusion modelDeep learning denoisingPET image qualityImage qualityVisual image qualityArea under the ROC curveActivity concentration ratioLow-contrast lesionsOverall image appearanceNoisy imagesImage representationLearning denoisingDenoisingHigh-contrast featuresNoise levelLesion uptakeLesion-to-background ratioInput noise levelTOF-OSEMDetection task
News
News
- June 30, 2026
Women’s Health Research at Yale and SWHR’s Symposium Highlights the Power of Collaboration to Advance Women’s Health Research
- March 26, 2026Source: CASE
Connecticut Academy of Science and Engineering Elects 36 New Members in 2026
- March 13, 2026
Connecticut Academy of Science and Engineering Elects Eight From YSM
- February 24, 2026
America’s First X-Ray: How Yale Advanced Medical Imaging
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