2022
Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment
Petersen G, Shatalov J, Verma T, Brim WR, Subramanian H, Brackett A, Bahar RC, Merkaj S, Zeevi T, Staib LH, Cui J, Omuro A, Bronen RA, Malhotra A, Aboian MS. Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment. American Journal Of Neuroradiology 2022, 43: 526-533. PMID: 35361577, PMCID: PMC8993193, DOI: 10.3174/ajnr.a7473.Peer-Reviewed Original ResearchConceptsMachine learning-based methodsLearning-based methodsBalanced data setData setsVector machine modelMachine learningClassification algorithmsMachine modelMachineAlgorithmData basesPrediction modelPromising resultsPrimary CNS lymphomaPrediction model study RiskRisk of biasRadiomic featuresClassifierSetCNS lymphomaWebLearningFeaturesQualitySystematic review
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
2003
Computing 3D Non-rigid Brain Registration Using Extended Robust Point Matching for Composite Multisubject fMRI Analysis
Papademetris X, Jackowski A, Schultz R, Staib L, Duncan J. Computing 3D Non-rigid Brain Registration Using Extended Robust Point Matching for Composite Multisubject fMRI Analysis. Lecture Notes In Computer Science 2003, 2879: 788-795. DOI: 10.1007/978-3-540-39903-2_96.Peer-Reviewed Original ResearchRobust Point MatchingIntensity-based registrationLarge point setsPoint matchingGreater computational efficiencyComputational efficiencyRobust pointSuperior performancePoint setsMagnetic resonance imagesBrain registrationActivation mapsFunctional magnetic resonance imagesSuccessful applicationRegistrationResonance imagesAlgorithmMatchingSpecificationMethodologyImagesRobustnessFrameworkSpecific areasSet
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
2000
Physical model-based non-rigid registration incorporating statistical shape information
Wang Y, Staib L. Physical model-based non-rigid registration incorporating statistical shape information. Medical Image Analysis 2000, 4: 7-20. PMID: 10972317, DOI: 10.1016/s1361-8415(00)00004-9.Peer-Reviewed Original ResearchConceptsStatistical shape informationStatistical shape modelDeformable elastic solidsComplex anatomical detailsIntensity similarity measureShape modelBayesian formulationBoundary shape informationViscous fluidCorresponding boundary pointsElastic solidsBoundary pointsDense setPhysical modelRobust approachSparse setReal medical imagesNumber of experimentsFirst methodShape informationSimilarity measureSetPhysical propertiesModelSmoothness
1998
Elastic model based non-rigid registration incorporating statistical shape information
Wang Y, Staib L. Elastic model based non-rigid registration incorporating statistical shape information. Lecture Notes In Computer Science 1998, 1496: 1162-1173. DOI: 10.1007/bfb0056306.Peer-Reviewed Original ResearchStatistical shape informationStatistical shape modelComplex anatomical detailsIntensity similarity measureShape modelElastic modelBayesian formulationBoundary shape informationCorresponding boundary pointsBoundary pointsDense setPhysical modelSparse setReal medical imagesNumber of experimentsShape informationRobust non-rigid registrationNew methodSimilarity measureModelSet