2024
A scalable approach to topic modelling in single-cell data by approximate pseudobulk projection
Subedi S, Sumida T, Park Y. A scalable approach to topic modelling in single-cell data by approximate pseudobulk projection. Life Science Alliance 2024, 7: e202402713. PMID: 39107066, PMCID: PMC11303850, DOI: 10.26508/lsa.202402713.Peer-Reviewed Original ResearchConceptsCell type-specific marker genesSingle-cell RNA-seq data analysisRNA-seq data analysisSingle-cell data analysisTopic modelsSingle-cell dataProbabilistic topic modelPathway annotationScalable approximation methodsLow memory consumptionComputation timeCellular statesMarker genesDictionary matrixLatent representationSingle-cellMemory consumptionTopic assignmentsComputing unitsFrequency vectorSelection stepCellsData analysisScalable approachData matrix
2019
Computational-efficient cascaded neural network for CT image reconstruction
Wu D, Kim K, Fakhri G, Li Q. Computational-efficient cascaded neural network for CT image reconstruction. Progress In Biomedical Optics And Imaging 2019, 10948: 109485z-109485z-6. DOI: 10.1117/12.2511526.Peer-Reviewed Original ResearchCascaded neural networkNeural networkImage reconstructionCT image reconstructionMemory consumptionDevelopment of deep learningDeep artificial neural networksState-of-the-artMedical image reconstructionReduce memory consumptionImage reconstruction qualitySparse-view samplingTraining ground truthUnrolling networkImage priorsImage quality improvementImage patchesReconstruction qualityDeep learningArtificial neural networkImage domainUndersampled projectionsTraining phaseTraining processParameter tuning
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