2018
2-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
2016
Towards patient-specific modeling of mitral valve repair: 3D transesophageal echocardiography-derived parameter estimation
Zhang F, Kanik J, Mansi T, Voigt I, Sharma P, Ionasec RI, Subrahmanyan L, Lin BA, Sugeng L, Yuh D, Comaniciu D, Duncan J. Towards patient-specific modeling of mitral valve repair: 3D transesophageal echocardiography-derived parameter estimation. Medical Image Analysis 2016, 35: 599-609. PMID: 27718462, DOI: 10.1016/j.media.2016.09.006.Peer-Reviewed Original ResearchConceptsMitral valve modelingTemporal informationPatient-specific modelingImage acquisitionEuclidean distanceValve modelingComputational frameworkExtended Kalman filterImage analysisModeling frameworkKalman filterFrameworkAverage errorMitral valve geometryTEE imagesInformationMachineParameter estimationClosed mitral valveLeaflet material propertiesSubjective predictionModelingImagesRepresentationOptimization