2023
Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts
You C, Dai W, Min Y, Staib L, Duncan J. Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts. Lecture Notes In Computer Science 2023, 14222: 561-571. PMID: 38840671, PMCID: PMC11151725, DOI: 10.1007/978-3-031-43898-1_54.Peer-Reviewed Original ResearchMedical image segmentationImage segmentationSegmentation methodPixel-level featuresComputer graphics problemImplicit neural representationsGrid-based representationMedical segmentationRendering frameworkSegmentation predictionsEnd mannerCorrelated contentCompetitive performance improvementsGraphics problemsSegmentationPoint representationPerformance improvementRegular gridSuch informationRepresentationConvolution operatorsExpertsComplex signalsRenderingFeatures
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
2018
2-Channel Convolutional 3D Deep Neural Network (2CC3D) for FMRI Analysis: ASD Classification and Feature Learning
Li X, Dvornek NC, Papademetris X, Zhuang J, Staib LH, Ventola P, Duncan JS. 2-Channel Convolutional 3D Deep Neural Network (2CC3D) for FMRI Analysis: ASD Classification and Feature Learning. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2018, 2018: 1252-1255. PMID: 32983370, PMCID: PMC7519578, DOI: 10.1109/isbi.2018.8363798.Peer-Reviewed Original ResearchConvolutional neural networkNeural networkCNN convolutional layerSpatial featuresASD classificationDeep neural networksMean F-scoreTraditional machineFeature learningConvolutional layersInput formatF-scoreClassification modelTemporal informationNetworkWindow parametersImagesClassificationConvolutionalTemporal statisticsMachineLearningFeaturesFormatScheme