2025
Flexible 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 PMID: 40089973, 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 simulations
2024
PET 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 tomographyGateAdaptive Correspondence Scoring for Unsupervised Medical Image Registration
Zhang X, Stendahl J, Staib L, Sinusas A, Wong A, Duncan J. Adaptive Correspondence Scoring for Unsupervised Medical Image Registration. Lecture Notes In Computer Science 2024, 15096: 76-92. DOI: 10.1007/978-3-031-72920-1_5.Peer-Reviewed Original ResearchMedical image registrationAdaptation frameworkMedical image datasetsUnsupervised learning schemeAdaptive training schemeImage registrationError residualsSupervision signalsLearning schemeImage datasetsRegistration architectureIntensity constancyScore mapNoisy gradientsMedical imagesTraining schemeImage reconstructionPerformance degradationLambertian assumptionCorrespondence scoresLoss of correspondenceTraining objectivesDisplacement estimationImage acquisitionSchemeThe United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances by Discovery in Radiation Detection
Buchsbaum J, Capala J, Obcemea C, Keppel C, Asai M, Chen G, Christy M, Fakhri G, Gueye P, Pogue B, Ruckman L, Tourassi G, Vetter K, Zhao W, Squires A, Saboury B, Wang G, Domurat‐Sousa K, Weisenberger A. The United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances by Discovery in Radiation Detection. Medical Physics 2024, 51: 8654-8669. PMID: 39177300, PMCID: PMC11659064, DOI: 10.1002/mp.17333.Peer-Reviewed Original ResearchNational Institutes of HealthState-of-the-artApplication of artificial intelligenceDOE Office of ScienceArtificial intelligenceMedical care advancesImage reconstructionIn-person workshopsOffice of ScienceRadiation detectionHealth collaborationInstitutes of HealthCare advancesIn-personAreas of successSparsity 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 signalsRemovalHankelEncoding scheme design for gradient-free, nonlinear projection imaging using Bloch-Siegert RF spatial encoding in a low-field, open MRI system
Selvaganesan K, Ha Y, Sun H, Zhang Z, Sun C, Samardzija A, Galiana G, Constable R. Encoding scheme design for gradient-free, nonlinear projection imaging using Bloch-Siegert RF spatial encoding in a low-field, open MRI system. Scientific Reports 2024, 14: 3307. PMID: 38332252, PMCID: PMC10853509, DOI: 10.1038/s41598-024-53703-y.Peer-Reviewed Original ResearchConceptsBloch-SiegertSpatial encodingBloch-Siegert shiftGradient-freeLow-field imagesLow fieldsProjection imagesPhase shiftLoop coilEncoding settingsEncoding schemeEncoding trajectoriesLow-field MR imagingSpatial resolutionImage reconstructionOptimization algorithmEncodingMRI systemShift effectHardware setupMR systemOpen MRI systemScheme designAlgorithmImages
2023
Cross-Attention for Improved Motion Correction in Brain PET
Cai Z, Zeng T, Lieffrig E, Zhang J, Chen F, Toyonaga T, You C, Xin J, Zheng N, Lu Y, Duncan J, Onofrey J. Cross-Attention for Improved Motion Correction in Brain PET. Lecture Notes In Computer Science 2023, 14312: 34-45. PMID: 38174216, PMCID: PMC10758996, DOI: 10.1007/978-3-031-44858-4_4.Peer-Reviewed Original ResearchDeep learning networkCross-attention mechanismDeep learning benchmarksMotion correctionTraining data domainPET list-mode dataPET image reconstructionQuality of reconstructionData domainCross attentionLearning networkSupervised mannerLearning benchmarksReference imageMotion trackingInherent informationList-mode dataImage reconstructionBrain PET dataPrediction resultsDifferent scannersHead motionImproved motion correctionNetworkSpatial correspondenceTransformer-Based Dual-Domain Network for Few-View Dedicated Cardiac SPECT Image Reconstructions
Xie H, Zhou B, Chen X, Guo X, Thorn S, Liu Y, Wang G, Sinusas A, Liu C. Transformer-Based Dual-Domain Network for Few-View Dedicated Cardiac SPECT Image Reconstructions. Lecture Notes In Computer Science 2023, 14229: 163-172. DOI: 10.1007/978-3-031-43999-5_16.Peer-Reviewed Original ResearchDual-domain networkSPECT image reconstructionImage reconstructionDeep learning methodsPrevious baseline methodsCardiac SPECT imagesHigh-quality imagesReconstruction networkIterative reconstruction processView reconstructionBaseline methodsReconstruction outputLearning methodsClinical softwareReconstruction processImaging problemsProjection dataImage qualityNetworkImagesStationary dataSPECT scannerDiagnosis of CVDLimited amountSoftwareBrain imaging with portable low-field MRI
Kimberly W, Sorby-Adams A, Webb A, Wu E, Beekman R, Bowry R, Schiff S, de Havenon A, Shen F, Sze G, Schaefer P, Iglesias J, Rosen M, Sheth K. Brain imaging with portable low-field MRI. Nature Reviews Bioengineering 2023, 1: 617-630. PMID: 37705717, PMCID: PMC10497072, DOI: 10.1038/s44222-023-00086-w.Peer-Reviewed Original ResearchSparse k-space dataK-space dataImage reconstructionUseful diagnostic imagesReconstruction algorithmLow power requirementsNew applicationsLF-MRIDiagnostic imagesNew approachNew opportunitiesHardwareConventional systemMachineOngoing developmentPower requirementsAlgorithmImagesTechnological innovationFurther innovationNoise cancellationNoise ratioTechnologyRequirementsInformationDirect estimation of metabolite maps from undersampled k-space data using linear tangent space alignment
Ma C, Marin T, Han P, El Fakhri G. Direct estimation of metabolite maps from undersampled k-space data using linear tangent space alignment. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2023 DOI: 10.58530/2023/0496.Peer-Reviewed Original ResearchArterial spin labeled perfusion imaging with balanced steady-state free precession readout and radial sampling
Han P, Marin T, Zhuo Y, Ouyang J, El Fakhri G, Ma C. Arterial spin labeled perfusion imaging with balanced steady-state free precession readout and radial sampling. Magnetic Resonance Imaging 2023, 102: 126-132. PMID: 37187264, PMCID: PMC10524790, DOI: 10.1016/j.mri.2023.05.005.Peer-Reviewed Original ResearchConceptsOff-resonance effectsBalanced steady-state free precessionPhase-cycling techniqueTemporal SNRBalanced steady-state free precession acquisitionRadial sampling schemeSpoiled gradient-recalled acquisitionRadial samplingCartesian sampling schemeBalanced steady-state free precession readoutK-space dataSampling schemeSpin labelingSteady-state free precessionK-spaceImage readoutBanding artifactsMotion-related artifactsReadoutFree precessionArterial spin labelingImage reconstructionParallel imagingImaging timePerfusion-weighted imagingDirect respiratory motion correction of whole-body PET images using a deep learning framework incorporating spatial information
Miao T, Tsai Y, Zhou B, Menard D, Schleyer P, Hong I, Casey M, Liu C. Direct respiratory motion correction of whole-body PET images using a deep learning framework incorporating spatial information. Progress In Biomedical Optics And Imaging 2023, 12463: 124633x-124633x-9. DOI: 10.1117/12.2654472.Peer-Reviewed Original ResearchDeep learning frameworkRespiratory motion correctionMotion-corrected imagesLearning frameworkImage domainSpatial informationData-driven gating methodMotion correctionMotion detection techniqueGround truth imagesU-NetTruth imagesPET imagesData driving methodImage reconstructionWhole-body PET imagesMotion sensorsDetection techniquesExternal motion sensorsCross validationImagesConvenient mannerFrameworkRespiratory motionInformationAAPM Task Group Report 238: 3D C‐arms with volumetric imaging capability*
Supanich M, Siewerdsen J, Fahrig R, Farahani K, Gang G, Helm P, Jans J, Jones K, Koenig T, Kuhls-Gilcrist A, Lin M, Riddell C, Ritschl L, Schafer S, Schueler B, Silver M, Timmer J, Trousset Y, Zhang J. AAPM Task Group Report 238: 3D C‐arms with volumetric imaging capability*. Medical Physics 2023, 50: e904-e945. PMID: 36710257, PMCID: PMC11584023, DOI: 10.1002/mp.16245.Peer-Reviewed Original ResearchConceptsImage qualityGeometric calibrationSystem calibrationPhantom imagesService callsC-arm systemImage reconstructionVolumetric imaging capabilityImage acquisitionGeometric alignmentImage-guided radiation therapyData setsTesting approachCBCT systemC-arm cone beamC-armReconstruction characteristicsImage artifactsValuable dataC-arm CBCT systemImagesIGRT systemTask groupDifferent systemsCT image qualityTracing Hot Spot Motion in Sagittarius A* Using the Next-Generation Event Horizon Telescope (ngEHT)
Emami R, Tiede P, Doeleman S, Roelofs F, Wielgus M, Blackburn L, Liska M, Chatterjee K, Ripperda B, Fuentes A, Broderick A, Hernquist L, Alcock C, Narayan R, Smith R, Tremblay G, Ricarte A, Sun H, Anantua R, Kovalev Y, Natarajan P, Vogelsberger M. Tracing Hot Spot Motion in Sagittarius A* Using the Next-Generation Event Horizon Telescope (ngEHT). Galaxies 2023, 11: 23. DOI: 10.3390/galaxies11010023.Peer-Reviewed Original ResearchCurrent sheetArray configurationHot spotsImage reconstruction algorithmShearing phaseSpot motionSecond phaseSgr AMore simulationsParticular simulationMotionSimulationsReconstruction algorithmSheetsImage reconstructionEvent Horizon TelescopeAxes ratioFirst phasePhaseBlack hole horizonArrayExhaustTelescope ArrayMagnetic reconnectionSagittarius A
2022
Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling
Djebra Y, Marin T, Han P, Bloch I, Fakhri G, Ma C. Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling. IEEE Transactions On Medical Imaging 2022, 42: 158-169. PMID: 36121938, PMCID: PMC10024645, DOI: 10.1109/tmi.2022.3207774.Peer-Reviewed Original ResearchConceptsSpace alignmentSampled k-space dataState-of-the-art methodsIntrinsic low-dimensional manifold structureNumerical simulation studyLow-dimensional manifold structureState-of-the-artLinear subspace modelSparsity modelModel-based frameworkSubspace modelManifold structureMathematical modelManifold modelSparse samplingImage reconstructionMRI applicationsDynamic magnetic resonance imagingSpatiotemporal signalsSpatial resolutionPerformanceSimulation studyImagesMethodSparsityOptimization of Design Parameters of Flat Panel Limited Angle TOF-PET Scanner: a Simulation Study
Orehar M, Dolenec R, Fakhri G, Gascón D, Gola A, Korpar S, Križan P, Razdevšek G, Pestotnik R. Optimization of Design Parameters of Flat Panel Limited Angle TOF-PET Scanner: a Simulation Study. 2022, 00: 1-4. DOI: 10.1109/nss/mic44845.2022.10399330.Peer-Reviewed Original ResearchImage quality phantomFlat-panel detectorGATE softwareRing scannerPanel detectorDetection chainState-of-the-artNEMA standardsOpen geometryImage reconstructionReconstructed imagesPositron emission tomographyState-of-the-art scannersScannerPhantomDetectorPhotodetectorsElectronNEMAMaterial costGatePositron
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