2023
Transformer-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 amountSoftware
2022
Increasing angular sampling through deep learning for stationary cardiac SPECT image reconstruction
Xie H, Thorn S, Chen X, Zhou B, Liu H, Liu Z, Lee S, Wang G, Liu YH, Sinusas AJ, Liu C. Increasing angular sampling through deep learning for stationary cardiac SPECT image reconstruction. Journal Of Nuclear Cardiology 2022, 30: 86-100. PMID: 35508796, DOI: 10.1007/s12350-022-02972-z.Peer-Reviewed Original ResearchConceptsDeep learningReconstruction qualityImage reconstructionDeep learning methodsDeep neural networksDeep learning resultsImage qualityNetwork trainingSPECT image reconstructionNeural networkLearning methodsHigh image resolutionImage volumesClinical softwareImage metricsImage resolutionReconstruction resultsImproved image qualityTesting dataLearning resultsNetwork resultsPhysical phantomStationary imagingDifferent subjectsLearning
2016
SPECT Imaging of 2-D and 3-D Distributed Sources with Near-Field Coded Aperture Collimation: Computer Simulation and Real Data Validation
Mu Z, Dobrucki LW, Liu YH. SPECT Imaging of 2-D and 3-D Distributed Sources with Near-Field Coded Aperture Collimation: Computer Simulation and Real Data Validation. Journal Of Medical And Biological Engineering 2016, 36: 32-43. PMID: 27069461, PMCID: PMC4791458, DOI: 10.1007/s40846-016-0111-6.Peer-Reviewed Original ResearchMaximum likelihood expectation maximizationReconstruction approachImage resolutionLarge projection angleIterative image reconstructionNoise artifactsMicro-SPECT systemComputer simulationsReal data validationImage reconstructionDigital phantomExpectation maximizationData validationCA moduleMLEM algorithmImage qualityPinhole imagesProjection angleCommercial softwareImagesPhantom imagesSquared errorSPECT imagesCA imagesImage contrast
2006
Aperture Collimation Correction and Maximum-Likelihood Image Reconstruction for Near-Field Coded Aperture Imaging of Single Photon Emission Computerized Tomography
Mu Z, Liu YH. Aperture Collimation Correction and Maximum-Likelihood Image Reconstruction for Near-Field Coded Aperture Imaging of Single Photon Emission Computerized Tomography. IEEE Transactions On Medical Imaging 2006, 25: 701-711. PMID: 16768235, DOI: 10.1109/tmi.2006.873298.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtifactsData Interpretation, StatisticalFeasibility StudiesHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalInformation Storage and RetrievalLikelihood FunctionsPhantoms, ImagingReproducibility of ResultsSensitivity and SpecificityTomography, Emission-Computed, Single-PhotonConceptsX-ray astronomySingle projectionCA imagesCoded Aperture ImagingMLEM reconstruction algorithmNear-field artifactsCollimation effectMaximum-likelihood image reconstructionSPECT systemParallel-hole collimatorImage reconstruction methodImage resolutionAperture imagingCollimationDeconvolution methodDual acquisitionImage reconstructionCount sensitivityImaging techniquesPhoton emissionPinholesReconstruction algorithm
1995
Blind deconvolution of fluorescence micrographs by maximum-likelihood estimation.
Krishnamurthi V, Liu Y, Bhattacharyya S, Turner J, Holmes T. Blind deconvolution of fluorescence micrographs by maximum-likelihood estimation. Applied Optics 1995, 34: 6633-47. PMID: 21060518, DOI: 10.1364/ao.34.006633.Peer-Reviewed Original ResearchReal image reconstructionReconstructed imagesBlind deconvolutionImage dataBlind deconvolution algorithmAlgorithmic refinementsBlind deconvolution methodPoint spread functionSame data setImage reconstructionReconstructed point spread functionsAlgorithmData setsImagesBlind versionSmear removalConfocal dataComputer simulationsMaximum likelihood estimationDeblurringFluorescence micrographs
1993
Three-dimensional image reconstruction of fluorescence micrographs without knowing the point spread function
Holmes T, Krishnamurthi V, Liu Y. Three-dimensional image reconstruction of fluorescence micrographs without knowing the point spread function. Microscopy And Microanalysis 1993, 51: 152-153. DOI: 10.1017/s0424820100146606.Peer-Reviewed Original ResearchGeneral signal processing applicationsSignal processing applicationsBlind deconvolutionImage dataProcessing applicationsPoint spread functionNoisy dataImage reconstructionThree-dimensional image reconstructionBlind deconvolution approachOptimization approachExplicit knowledgeSpread functionMaximum likelihood estimationMathematical optimization approachNew approach