2024
Federated Privacy-Preserving Visualization: A Vision Paper
Tao Y, Sarwate A, Panta S, Plis S, Calhoun V. Federated Privacy-Preserving Visualization: A Vision Paper. 2024, 00: 8035-8041. DOI: 10.1109/bigdata62323.2024.10825849.Peer-Reviewed Original ResearchFederated learningRisk of data leakagePrivacy-preserving techniquesDifferential privacyData leakageSensitive informationVision paperFL applicationsModel trainingData visualizationExploratory data analysisCorrelation visualizationCentralized systemPrivacyLocal dataVisualizationDistribution dataData analysisMonitoring dataTaskDataLearningImplementationVisionInformationEfficient federated learning for distributed neuroimaging data
Thapaliya B, Ohib R, Geenjaar E, Liu J, Calhoun V, Plis S. Efficient federated learning for distributed neuroimaging data. Frontiers In Neuroinformatics 2024, 18: 1430987. PMID: 39315000, PMCID: PMC11416982, DOI: 10.3389/fninf.2024.1430987.Peer-Reviewed Original ResearchFederated learningCommunication overheadsSparse modelModel sparsityClient siteTraining phaseAdolescent Brain Cognitive DevelopmentData sharingEfficient communicationLarge modelsLocal trainingResource capabilitiesDatasetCommunicationLearningSparsityActual dataOverheadsPrivacyNeuroimaging dataCognitive developmentDataScientific communitySharingCGDM-GAN: An Adversarial Network Approach with Self-supervised Learning for Site Effect Removal
Cui X, Zhi D, Yan W, Calhoun V, Zhuo C, Sui J. CGDM-GAN: An Adversarial Network Approach with Self-supervised Learning for Site Effect Removal. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039732, DOI: 10.1109/embc53108.2024.10782176.Peer-Reviewed Original ResearchConceptsSelf-supervised learningIntrinsic image propertiesGeneralization of modelsSynthetic datasetsClassification performanceGenerative modelDiscrepancy minimizationImage dataNetwork approachDatasetData harmonizationImaging propertiesLearningNeuroimaging classificationCycleGANData harmonization methodsAdversaryABCD datasetAcquisition protocolsPerformanceEffective wayDataTaskExploring Schizophrenia Classification in fMRI Data: A Common Spatial Patterns(CSP) Approach for Enhanced Feature Extraction and Classification
Esfahani M, Miller R, Calhoun V. Exploring Schizophrenia Classification in fMRI Data: A Common Spatial Patterns(CSP) Approach for Enhanced Feature Extraction and Classification. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40040201, DOI: 10.1109/embc53108.2024.10782387.Peer-Reviewed Original ResearchConceptsImplementation of deep learning modelsNetwork connectivityUnsupervised dimensionality reduction techniquesTime-varying network connectivityEnhanced feature extractionDimensionality reduction techniquesDeep learning modelsMotor imagery tasksFeature extractionElectroencephalogram signalsTransformation of signalsEEG signalsPrincipal component analysisLearning modelsData typesCSP methodApplication of CSPSchizophrenia classificationFMRI datasetsReduction techniquesImagery tasksDatasetCSPDataClassificationPrivacy-Preserving Visualization of Brain Functional Network Connectivity
Tao Y, Sarwate A, Panta S, Plis S, Calhoun V. Privacy-Preserving Visualization of Brain Functional Network Connectivity. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635222.Peer-Reviewed Original ResearchDifferential privacyProtecting sensitive informationNon-private counterpartsPre-and post-processingPrivacy-preservingPrivacy guaranteesSensitive informationPrivacy costData visualizationPrivacyBiomedical dataInvestigate several approachesNetwork connectivityPost-processingSeveral approachesVisualizationWorkflowGuaranteesCorrelation valuesTradeoffDataConnectogramsInformationImproving Age Prediction: Utilizing LSTM-Based Dynamic Forecasting For Data Augmentation in Multivariate Time Series Analysis
Gao Y, Ellis C, Calhoun V, Miller R. Improving Age Prediction: Utilizing LSTM-Based Dynamic Forecasting For Data Augmentation in Multivariate Time Series Analysis. 2024, 00: 125-128. DOI: 10.1109/ssiai59505.2024.10508611.Peer-Reviewed Original ResearchLong short-term memoryDeep learning modelsData augmentationPerformance deep learning modelsLearning modelsMultivariate time series dataAge prediction taskShort-term memoryPrediction taskAugmented datasetDynamical forecastsComponent networksMultivariate time series analysisDatasetNeuroimaging datasetsRobust solutionTime series dataOriginal dataValidation frameworkTime series analysisSeries dataNetworkNeuroimaging fieldDataModel performanceDecentralized Mixed Effects Modeling in COINSTAC
Basodi S, Raja R, Gazula H, Romero J, Panta S, Maullin-Sapey T, Nichols T, Calhoun V. Decentralized Mixed Effects Modeling in COINSTAC. Neuroinformatics 2024, 22: 163-175. PMID: 38424371, DOI: 10.1007/s12021-024-09657-7.Peer-Reviewed Original ResearchLarge-scale analysis of dataDecentralized platformLow bandwidthData transferMemory requirementsData sharingSubstantial overheadsCOINSTACStructural magnetic resonance imagingNeuroimaging communityDataData poolNeuroimaging analysisOverheadsPrivacyLarge-scale analysisImagesMagnetic resonance imagingGray matter reductionsMedial frontal regionsDimensionalityLinear mixed-effectsModeling approachBandwidthResearch groupsIdentifying the Relationship Structure Among Multiple Datasets Using Independent Vector Analysis: Application to Multi-Task fMRI Data
Lehmann I, Hasija T, Gabrielson B, Akhonda M, Calhoun V, Adali T. Identifying the Relationship Structure Among Multiple Datasets Using Independent Vector Analysis: Application to Multi-Task fMRI Data. IEEE Access 2024, 12: 109443-109456. DOI: 10.1109/access.2024.3435526.Peer-Reviewed Original ResearchIndependent vector analysisTask datasetMultiple datasetsFeature extraction approachUser-defined thresholdsHigher-order statisticsMulti-task fMRI dataExtraction approachRelationship structureDatasetSimulation resultsHierarchical clusteringInterpretable componentsVector analysisFMRI-dataFMRI dataEffective wayMethodTaskDataActivated brain regionsHypothesis testingDistributional assumptionsInformation
2023
CfMRIPrep: A MATLAB toolbox for integrated preprocessing of complex-valued fMRI data
Li S, Ma M, Lin Q, Calhoun V. CfMRIPrep: A MATLAB toolbox for integrated preprocessing of complex-valued fMRI data. 2023, 00: 167-171. DOI: 10.1109/icist59754.2023.10367157.Peer-Reviewed Original ResearchComplex-valued fMRI dataPhase fMRI dataMATLAB toolboxFMRIB Software LibraryNew MATLAB toolboxMotion correctionSoftware libraryManual approachFMRI dataExperimental resultsHead motionPhase unwrappingSpatial normalizationToolboxDifferent subjectsPhase dataMagnitude dataPreprocessingDataProcessingUnwrappingLibraryFlexible Multisubject Multiset FMRI Data Analysis Using Robust Discriminative Dictionary Learning
Jin R, Xu S, Kim S, Calhoun V. Flexible Multisubject Multiset FMRI Data Analysis Using Robust Discriminative Dictionary Learning. 2023, 00: 1458-1462. DOI: 10.1109/ieeeconf59524.2023.10476781.Peer-Reviewed Original ResearchDictionary learning methodDiscriminative dictionary learningGroup sparsity constraintData setsDictionary learningAttribute labelsSparsity constraintLearning methodsFMRI data setsNeural activation mapsPre-specifyingActivation mapsMap typesFunctional magnetic resonance imagingNumerical testsMapsDictionaryAlgorithmSetsDataLearningSubject-specific attributesMethodData analysisConstraintsMultimodal Subspace Independent Vector Analysis Better Captures Hidden Relationships in Multimodal Neuroimaging Data
Li X, Adali T, Silva R, Calhoun V. Multimodal Subspace Independent Vector Analysis Better Captures Hidden Relationships in Multimodal Neuroimaging Data. 2023, 00: 1-5. DOI: 10.1109/isbi53787.2023.10230605.Peer-Reviewed Original ResearchSubspace structureIndependent vector analysisSynthetic datasetsMultimodal neuroimaging datasetUnimodal analysisData modalitiesHidden relationshipsCanonical correlation analysisIncorrect onesNeuroimaging datasetsSubspaceLatent sourcesDatasetNeuroimaging modalitiesDataPhenotypic measurementsCorrelation analysis
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply