2020
Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification
Zhang F, Dvornek N, Yang J, Chapiro J, Duncan J. Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification. IEEE Transactions On Medical Imaging 2020, 39: 3331-3342. PMID: 32356739, PMCID: PMC7606489, DOI: 10.1109/tmi.2020.2990625.Peer-Reviewed Original ResearchConceptsConvolutional neural networkNeural networkClassification taskProbability calibrationTissue classification tasksImage representationBaseline methodsPublic datasetsModel performanceRandom forest modelNetworkBetter performanceForest modelDatasetClassificationTaskCT imagesImagesOriginal model outputMR imagesModel outputInstitutional datasetPerformanceEmbeddingOutputDemographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity
Dvornek NC, Li X, Zhuang J, Ventola P, Duncan JS. Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity. Lecture Notes In Computer Science 2020, 12436: 363-372. PMID: 34308438, PMCID: PMC8299434, DOI: 10.1007/978-3-030-59861-7_37.Peer-Reviewed Original ResearchRecurrent neural network modelRecurrent neural networkNeural network modelFunctional magnetic resonance imaging (fMRI) time series dataAttention mechanismArt resultsNeural networkCross-validation frameworkNetwork modelTime series dataIndividual demographic informationABIDE IImproved classificationNetwork differencesNetworkClassificationFunctional network differencesFrameworkIndividual demographic variablesInformation
2019
Invertible Network for Classification and Biomarker Selection for ASD
Zhuang J, Dvornek NC, Li X, Ventola P, Duncan JS. Invertible Network for Classification and Biomarker Selection for ASD. Lecture Notes In Computer Science 2019, 11766: 700-708. PMID: 32274471, PMCID: PMC7144624, DOI: 10.1007/978-3-030-32248-9_78.Peer-Reviewed Original ResearchInvertible networksDeep learning methodsDeep learning modelsBlack-box natureLowest regression errorRegression tasksClassification taskLearning methodsLearning modelDecision boundariesModel decisionsImportant edgesLinear classifierConnectivity matrixASD classificationNetworkBlack-box representationBiomarker selectionRegression errorsData pointsImportance measuresTaskNovel methodClassificationClassifier
2018
Liver Tissue Classification Using an Auto-context-based Deep Neural Network with a Multi-phase Training Framework
Zhang F, Yang J, Nezami N, Laage-gaupp F, Chapiro J, De Lin M, Duncan J. Liver Tissue Classification Using an Auto-context-based Deep Neural Network with a Multi-phase Training Framework. Lecture Notes In Computer Science 2018, 11075: 59-66. PMID: 32432233, PMCID: PMC7236808, DOI: 10.1007/978-3-030-00500-9_7.Peer-Reviewed Original ResearchNeural networkNovel deep convolutional neural networkStandard neural network approachesTraining frameworkDeep convolutional neural networkU-Net-like architectureTissue classificationConvolutional neural networkDeep neural networksNeural network approachSegmentation masksBenchmark methodsNetwork approachPatch-based strategyLearning spacesLiver tissue classificationMagnetic resonance imagesPromising resultsNetworkImagesPredictive modelClassificationFrameworkResonance imagesArchitecture2-Channel Convolutional 3D Deep Neural Network (2CC3D) for FMRI Analysis: ASD Classification and Feature Learning
Li X, Dvornek NC, Papademetris X, Zhuang J, Staib LH, Ventola P, Duncan JS. 2-Channel Convolutional 3D Deep Neural Network (2CC3D) for FMRI Analysis: ASD Classification and Feature Learning. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2018, 2018: 1252-1255. PMID: 32983370, PMCID: PMC7519578, DOI: 10.1109/isbi.2018.8363798.Peer-Reviewed Original ResearchConvolutional neural networkNeural networkCNN convolutional layerSpatial featuresASD classificationDeep neural networksMean F-scoreTraditional machineFeature learningConvolutional layersInput formatF-scoreClassification modelTemporal informationNetworkWindow parametersImagesClassificationConvolutionalTemporal statisticsMachineLearningFeaturesFormatScheme