2024
Flat 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 tomographyGate
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 studyImagesMethodSparsity