2018
Deep Learning Retinal Vessel Segmentation from a Single Annotated Example: An Application of Cyclic Generative Adversarial Neural Networks
Sadda P, Onofrey J, Papademetris X. Deep Learning Retinal Vessel Segmentation from a Single Annotated Example: An Application of Cyclic Generative Adversarial Neural Networks. Lecture Notes In Computer Science 2018, 11043: 82-91. DOI: 10.1007/978-3-030-01364-6_10.Peer-Reviewed Original ResearchGenerative adversarial neural networksAdversarial neural networkGround truth segmentationNeural networkTruth segmentationMedical image segmentation tasksImage segmentation tasksConvolutional neural networkDeep learning methodsRetinal vessel segmentationConvolutional networkSegmentation taskTraining examplesAnnotated examplesTraining dataLearning methodsVessel segmentationSegmentationSynthetic examplesNetworkLarge amountDatasetTaskExampleAccuracy
2006
Combined Feature/Intensity-Based Brain Shift Compensation Using Stereo Guidance
DeLorenzo C, Papademetris X, Vives K, Spencer D, Duncan J. Combined Feature/Intensity-Based Brain Shift Compensation Using Stereo Guidance. 2006, 335-338. DOI: 10.1109/isbi.2006.1624921.Peer-Reviewed Original ResearchSoft tissue deformationBrain shift compensationImage-derived informationSurface displacementsTracking accuracySurface motionTissue deformationAppropriate model parametersShift compensationBrain motionReal surfacesBiomechanical modelStereo camera imagesModel parametersCompensation systemData tradeoffsBrain displacementDisplacementCamera imagesMotionDeformationAccuracyImage intensity