2014
Evaluating Structural Symmetry of Weighted Brain Networks via Graph Matching
Hu C, El Fakhri G, Li Q. Evaluating Structural Symmetry of Weighted Brain Networks via Graph Matching. Lecture Notes In Computer Science 2014, 17: 733-740. PMID: 25485445, DOI: 10.1007/978-3-319-10470-6_91.Peer-Reviewed Original ResearchConceptsAttention deficit hyperactivity disorderNetwork symmetryBrain networksType of Attention Deficit Hyperactivity DisorderWeighted brain networksConsistent with former findingsDeficit hyperactivity disorderRs-fMRI networksResting state fMRISymmetry levelInattentive typeHyperactivity disorderBrain areasSymmetryStructural symmetryBrain connectivityFunctional networksResting stateLarger thresholdsBrainFMRIHigher levelsGraph matchingNode pairsNormal subjects
2013
Matched Signal Detection on Graphs: Theory and Application to Brain Network Classification
Hu C, Cheng L, Sepulcre J, El Fakhri G, Lu Y, Li Q. Matched Signal Detection on Graphs: Theory and Application to Brain Network Classification. Lecture Notes In Computer Science 2013, 23: 1-12. PMID: 24683953, DOI: 10.1007/978-3-642-38868-2_1.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAlzheimer DiseaseAniline CompoundsBenzothiazolesBrainBrain MappingConnectomeHumansImage EnhancementImage Interpretation, Computer-AssistedNerve NetNeural PathwaysPattern Recognition, AutomatedPositron-Emission TomographyReproducibility of ResultsSensitivity and SpecificityThiazolesTissue DistributionConceptsBrain network classificationNetwork classification problemWeighted energy detectorPrinciple component analysisSub-manifold structureTraditional principle component analysisSubspace detectionTraining dataEnergy detectorGraph structureProblem of Alzheimer's diseaseGraph LaplacianNetwork classificationNoise varianceLevel of smoothnessWeighted graphSignal detectionIntrinsic structureSignal modelGraphSubspaceIsing modelNoiseSignal variationsComponent analysis