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 imagesArchitecture
2004
Geometric strategies for neuroanatomic analysis from MRI
Duncan JS, Papademetris X, Yang J, Jackowski M, Zeng X, Staib LH. Geometric strategies for neuroanatomic analysis from MRI. NeuroImage 2004, 23: s34-s45. PMID: 15501099, PMCID: PMC2832750, DOI: 10.1016/j.neuroimage.2004.07.027.Peer-Reviewed Original ResearchConceptsApplied mathematical approachWhite matter fiber tracksStatistical estimationMathematical approachFunction-structure analysisMagnetic resonance imagesEvolution strategyGeometric constraintsImage processingIntersubject registrationRich setGeometric strategyOngoing workData setsUse of levelsCommon spaceNeuroanatomic analysisSetRegistrationFiber tracksHuman brainResonance imagesInformationSegmentationEstimation