About
Titles
PET Engineer
Departments & Organizations
Research
Research at a Glance
Yale Co-Authors
Frequent collaborators of Tim Mulnix's published research.
Kathryn Fontaine
Jean-Dominique Gallezot, PhD
Richard Carson, PhD
Takuya Toyonaga, MD, PhD
David Matuskey, MD
Adam Mecca, MD, PhD
Publications
2024
Fast Energy-Based Scatter Correction for 3D TOF-PET on NeuroExplorer
Guo L, Fontaine K, Gravel P, Mulnix T, Zhang J, Liu C, Carson R. Fast Energy-Based Scatter Correction for 3D TOF-PET on NeuroExplorer. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10657901.Peer-Reviewed Original ResearchCitationsConceptsSingle scatter simulationScatter estimationEnergy spectrumTOF binsField of viewAxial field-of-viewHigh-energy scatteringLong axial field-of-viewLow-activity regionsList-mode dataEnergy informationTOF-PETContrast phantomUniform phantomScattering phantomCounting statisticsScatter correctionOSEM reconstructionMultiple-scatteringScatteringScattering simulationsPhantomEvent distributionImproved contrastMonte-CarloMOLAR-NX: building a PET reconstruction framework for exploring the novel features provided by the NeuroEXPLORER
Fontaine K, Gallezot J, Zhang J, He L, Gravel P, Zeng T, Li T, Li Y, Leung E, Sun X, Guo L, Mulnix T, Toyonaga T, Lu Y, Li H, Badawi R, Qi J, Carson R. MOLAR-NX: building a PET reconstruction framework for exploring the novel features provided by the NeuroEXPLORER. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10655187.Peer-Reviewed Original ResearchConceptsReconstruction processDepth of interactionReconstruction frameworkAdvanced frameworkFramework's effectivenessMask featuresNovel featuresContrast recoveryScatter correction methodReconstruction softwareFrameworkListmode dataDownsamplingMotion correctionPhantom studyListmode filesFeaturesCorrection methodSoftwareFilesNeuroExplorerReconstructionLarge human cohort study of markerless head motion tracking for brain PET
Zeng T, Zhang J, Gallezot J, Fontaine K, Gravel P, Jiang W, Mulnix T, Yang Z, Zhang X, Hu L, Carson R. Large human cohort study of markerless head motion tracking for brain PET. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10656091.Peer-Reviewed Original ResearchConceptsPost-reconstruction registrationEvent-by-eventBrain PET imagingMotion correction techniqueQuantitative PET imagingPET imagingBrain PETHead motionTime activity curvesStudy of brain functionImage qualityMotion tracking systemGray matter regionsCorrection techniqueMotionHuman cohort studiesAverage SUVPET measurementsMotion blurMatter regionsSuperior performanceTracking systemPolarisHigh-resolution brain phantom data, with flexible contrast: Validation on the NeuroExplorer (NX)
Gravel P, Toyonaga T, Gallezot J, Fontaine K, Martins S, Mulnix T, Carson R. High-resolution brain phantom data, with flexible contrast: Validation on the NeuroExplorer (NX). 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10656366.Peer-Reviewed Original ResearchConceptsQuantitative accuracyPhantom dataSpatial resolutionIterative reconstruction algorithmListmode dataAttenuation correctionPhantom studyPhantomResolution measurementsAttenuation propertiesReconstructed imagesReconstruction algorithmPET imagingCorrection accuracyResolutionScatteringAxial directionAttenuationContrastCorrectionImage-Derived Input Functions on an Ultra-High Performance Brain PET Scanner: Minimizing the Carotid Partial Volume Effect
Volpi T, Zeng T, Khattar N, Toyonaga T, Martins S, Mulnix T, Fontaine K, Gallezot J, Carson R. Image-Derived Input Functions on an Ultra-High Performance Brain PET Scanner: Minimizing the Carotid Partial Volume Effect. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10658264.Peer-Reviewed Original ResearchConceptsPerformance Characteristics of the NeuroEXPLORER, a Next-Generation Human Brain PET/CT Imager
Li H, Badawi R, Cherry S, Fontaine K, He L, Henry S, Hillmer A, Hu L, Khattar N, Leung E, Li T, Li Y, Liu C, Liu P, Lu Z, Majewski S, Matuskey D, Morris E, Mulnix T, Omidvari N, Samanta S, Selfridge A, Sun X, Toyonaga T, Volpi T, Zeng T, Jones T, Qi J, Carson R. Performance Characteristics of the NeuroEXPLORER, a Next-Generation Human Brain PET/CT Imager. Journal Of Nuclear Medicine 2024, 65: jnumed.124.267767. PMID: 38871391, PMCID: PMC11294061, DOI: 10.2967/jnumed.124.267767.Peer-Reviewed Original ResearchCitationsAltmetricConceptsPeak noise-equivalent count rateNoise-equivalent count rateTime-of-flight resolutionField of viewCount rateExtended axial field-of-viewTransverse field-of-viewAxial field-of-viewField-of-view centerMini-Derenzo phantomSpatial resolutionTangential spatial resolutionsCount rate performanceContrast recovery coefficientHuman brain PET imagingMeasurements of spatial resolutionNEMA sensitivityEnergy resolutionScatter fractionBrain phantomBackprojection reconstructionBrain PET imagingTime resolutionRadial offsetF-FDG imagingRelationship between neuroimaging and cognition in frontotemporal dementia: An FDG‐PET and structural MRI study
Cayir S, Volpi T, Toyonaga T, Gallezot J, Yang Y, Sadabad F, Mulnix T, Mecca A, Fesharaki‐Zadeh A, Matuskey D. Relationship between neuroimaging and cognition in frontotemporal dementia: An FDG‐PET and structural MRI study. Journal Of Neuroimaging 2024, 34: 627-634. PMID: 38676301, PMCID: PMC11511789, DOI: 10.1111/jon.13206.Peer-Reviewed Original ResearchAltmetricConceptsMoCA scoresFDG-PETAssociation of cognitionStandardized uptake value ratioMontreal Cognitive AssessmentSignificant positive associationFrontotemporal dementiaPrimary outcome measurePosterior cingulate cortexDecline of cognitive functionYears of ageGM volumeFrontal cortexOutcome measuresCognitive dysfunctionGray matterCognitive AssessmentMoCAAssociated with cognitive dysfunctionFluorodeoxyglucose (FDG)-PETPositive associationMagnetic resonance imagingPartial volume correctionCognitive functionDementia
2022
Event-by-Event 3D Continuous Motion Correction Based on a Data-Driven Motion Estimation Algorithm for 82Rb Myocardial Perfusion Imaging
Tsai Y, Fontaine K, Mulnix T, Armstrong I, Hayden C, Spottiswoode B, Casey M, Liu C. Event-by-Event 3D Continuous Motion Correction Based on a Data-Driven Motion Estimation Algorithm for 82Rb Myocardial Perfusion Imaging. 2022, 00: 1-4. DOI: 10.1109/nss/mic44845.2022.10399100.Peer-Reviewed Original ResearchConceptsMotion correctionData-driven motion estimationPET/CT scannerSuperior-inferior motionMotion effectsSilicon photomultipliersNEMA phantomReconstruction frameworkPET acquisitionReconstructed image qualityCardiac PETMotion estimation algorithmPatient datasetsImage qualityMyocardial perfusion imagingCorrectionMotion monitoringTemporal resolutionSiPMMotionPhotomultiplierMotion estimationMotion vectorsPhantomCorrection algorithm
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