DuDoDR-Net: Dual-domain data consistent recurrent network for simultaneous sparse view and metal artifact reduction in computed tomography
Zhou B, Chen X, Zhou SK, Duncan JS, Liu C. DuDoDR-Net: Dual-domain data consistent recurrent network for simultaneous sparse view and metal artifact reduction in computed tomography. Medical Image Analysis 2021, 75: 102289. PMID: 34758443, PMCID: PMC8678361, DOI: 10.1016/j.media.2021.102289.Peer-Reviewed Original ResearchConceptsRecurrent networksSevere streak artifactsRecurrent frameworkArtifact reductionSparse viewsImage domainReconstruction qualityCT metal artifact reductionX-ray projectionsMetal artifact reductionArtifact-free imagesMedical diagnosisPrevious methodsProjection dataConsistent layerExperimental resultsLimited View Tomographic Reconstruction Using a Cascaded Residual Dense Spatial-Channel Attention Network With Projection Data Fidelity Layer
Zhou B, Zhou S, Duncan JS, Liu C. Limited View Tomographic Reconstruction Using a Cascaded Residual Dense Spatial-Channel Attention Network With Projection Data Fidelity Layer. IEEE Transactions On Medical Imaging 2021, 40: 1792-1804. PMID: 33729929, PMCID: PMC8325575, DOI: 10.1109/tmi.2021.3066318.Peer-Reviewed Original ResearchConceptsAttention networkView reconstructionGrand challenge datasetLimited angle reconstructionHigh-quality reconstructionNeural network methodSparse-view reconstructionExperimental resultsLimited angle acquisitionArchitecture issuesSparse viewsChallenge datasetLimited view dataView dataNeural architectureQuality reconstructionNetwork methodTomographic reconstructionReconstructed imagesProjection viewsPrevious methodsAngle reconstructionDatasetNetworkAngle acquisition