2022
Learning Correspondences of Cardiac Motion from Images Using Biomechanics-Informed Modeling
Zhang X, You C, Ahn S, Zhuang J, Staib L, Duncan J. Learning Correspondences of Cardiac Motion from Images Using Biomechanics-Informed Modeling. Lecture Notes In Computer Science 2022, 13593: 13-25. DOI: 10.1007/978-3-031-23443-9_2.Peer-Reviewed Original ResearchDisplacement vector fieldQuantitative evaluation metricsCardiac anatomical structuresTraining complexityExtensive experimentsSegmentation performanceBiomechanical feasibilityEvaluation metricsAvailable datasetsCardiac motionSmoothness constraintGeometric constraintsBiomechanical propertiesDatasetMRI dataPlausible transformationsMotionConstraintsAnatomical structuresRegularizerRegularization schemeMethodIncompressibilityImagesMetrics
2002
Prior Shape Models for Boundary Finding
Staib L. Prior Shape Models for Boundary Finding. 2002, 30-33. DOI: 10.1109/isbi.2002.1029185.Peer-Reviewed Original ResearchBoundary findingTraining setAvailable training setPrior shape informationPrior informationPrior shape modelImage informationPrior shapeShape informationTarget objectBayesian formulationShape modelStatistical variationSmoothness constraintShape parametersNatural approachPosterior probabilityGeneric informationInformationObjectsAdditional flexibilitySetKey componentImagesSimilar shape