2025
Enhancing Uncertainty Estimation in Semantic Segmentation via Monte-Carlo Frequency Dropout
Zeevi T, Staib L, Onofrey J. Enhancing Uncertainty Estimation in Semantic Segmentation via Monte-Carlo Frequency Dropout. 2025, 00: 1-5. DOI: 10.1109/isbi60581.2025.10980684.Peer-Reviewed Original ResearchSemantic segmentationDeterministic neural networksChest X-ray scansFeature mapsTraditional dropoutSegmentation taskMC dropoutNeural networkMedical imagesSignal spaceSemantic uncertaintyContrast-enhanced CTEnhance medical decision-makingBiparametric MRIPractical solutionProstate zonesFrequency domainLiver tumorsMonte-CarloX-ray scansUncertainty estimationBoundary delineationMC frequencyTextural variationsImaging modalities
2024
Monte-Carlo Frequency Dropout for Predictive Uncertainty Estimation in Deep Learning
Zeevi T, Venkataraman R, Staib L, Onofrey J. Monte-Carlo Frequency Dropout for Predictive Uncertainty Estimation in Deep Learning. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635511.Peer-Reviewed Original ResearchArtificial neural networkState-of-the-artMedical image dataPredictive uncertainty estimationBiomedical image dataImage dataOptimal artificial neural networkMC dropoutDropout approachSource-codeDrop-connectDeep learningNeural networkSignal spaceMonte-CarloPrediction uncertaintyUncertainty estimationDiverse setComprehensive comparisonPrediction scenariosDeepPosterior predictive distributionRepositoryDecision-makingNetwork
2023
Simulation results for limited-angle ultra-high time-of-flight resolution PET system
Marin T, Zhuo Y, Orehar M, Razdevšekc G, Dolenec R, Mounime I, Alamo J, Benlloch J, Chemli Y, Fernández-Tenllado J, Gascon D, Gola A, Gomez S, Grogg K, Guberman D, Korpar S, Krizan P, Majewski S, Manera R, Mariscal-Castilla A, Mauricio J, Merzi S, Morera C, Normandin M, Pavon G, Penna M, Seljak A, Studen A, Pestotnik R, Fakhri G. Simulation results for limited-angle ultra-high time-of-flight resolution PET system. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10337821.Peer-Reviewed Original ResearchResolution PET systemsPET systemAxial fieldPositron emission tomography systemPositron emission tomography scannerTotal-body PET systemsLong axial fieldTOF resolutionNovel detectorNumerical phantomHigh-sensitivity systemMonte-Carlo simulationsSpatial resolutionPositron emission tomographyMonte-CarloSystem sensitivityImage resolutionImage qualityScintillationReconstruction engineFWHMResolutionTOFPhantomScanner
2021
First Investigation of List mode MLEM Reconstruction for Fast DC-SPECT System Design Optimization
Feng Y, Bläckberg L, Fakhri G, Worstell W, Sabet H. First Investigation of List mode MLEM Reconstruction for Fast DC-SPECT System Design Optimization. 2021, 00: 1-3. DOI: 10.1109/nss/mic44867.2021.9875864.Peer-Reviewed Original ResearchFWHM spatial resolutionCorrection of scatterAsymmetric geometryMaximum likelihood expectation maximizationLikelihood expectation maximizationSystem's imaging resolutionLM-MLEMMonte Carlo implementationMLEM reconstructionDetector headMonte-CarloSystem matrix modelSimultaneous high resolutionDesign optimizationCardiac SPECTMatrix modelSystem resolutionMC methodSpatial resolutionSystem design optimizationImage reconstructionDynamic cardiac SPECTDesign iterationsSystem sensitivityImage resolution
2013
Simultaneous 99mTc‐MDP/123I‐MIBG tumor imaging using SPECT‐CT: Phantom and constructed patient studies
Rakvongthai Y, Fakhri G, Lim R, Bonab A, Ouyang J. Simultaneous 99mTc‐MDP/123I‐MIBG tumor imaging using SPECT‐CT: Phantom and constructed patient studies. Medical Physics 2013, 40: 102506. PMID: 24089927, PMCID: PMC3785531, DOI: 10.1118/1.4820977.Peer-Reviewed Original ResearchConceptsScatter correctionDual-radionuclideContrast recoveryPhantom studyAnthropomorphic torso phantomPatient studiesTumor uptakeTumor imagingSPECT projectionsTorso phantomMonte-CarloPhantom dataPhantomIterative reconstructionOSEMProjection dataDR dataIncrease patient throughputNoise realizationsSPECT-CTImage reconstructionClinical studiesTumorTumor projectionPoisson noise
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply