2019
Generalizable Multi-Site Training and Testing Of Deep Neural Networks Using Image Normalization
Onofrey JA, Casetti-Dinescu DI, Lauritzen AD, Sarkar S, Venkataraman R, Fan RE, Sonn GA, Sprenkle PC, Staib LH, Papademetris X. Generalizable Multi-Site Training and Testing Of Deep Neural Networks Using Image Normalization. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2019, 00: 348-351. PMID: 32874427, PMCID: PMC7457546, DOI: 10.1109/isbi.2019.8759295.Peer-Reviewed Original ResearchDeep neural networksNeural networkDeep learning algorithmsProstate gland segmentationImage normalization methodGland segmentationLearning algorithmImage normalizationMulti-site dataIntensity normalization methodNormalization methodSingle-site dataAlgorithmNetworkPotential solutionsEquipment sourcesClinical adoptionSegmentationTrainingIntensity characteristicsRobustnessDataSite trainingMethodAdoption
2011
Integrated Parcellation and Normalization Using DTI Fasciculography
Ho HP, Wang F, Papademetris X, Blumberg HP, Staib LH. Integrated Parcellation and Normalization Using DTI Fasciculography. Lecture Notes In Computer Science 2011, 14: 33-41. PMID: 21995010, PMCID: PMC3701295, DOI: 10.1007/978-3-642-23629-7_5.Peer-Reviewed Original ResearchConceptsDiffusion magnetic resonance imagesExtensive human interventionCumulative tracking errorsInteractive speedHuman interventionOrientation informationImage noiseMagnetic resonance imagesTracking errorVirtual pathwaysNormalization methodImagesDiffusion imagesWhite matter fasciclesFiber trackingCross-subject statisticsResonance imagesNew techniqueTrackingErrorVisualizationImplementationConnectivityInformationParcellation