Deep learning for prediction of post-thrombectomy outcomes based on admission CT angiography in large vessel occlusion stroke
Sommer J, Dierksen F, Zeevi T, Tran A, Avery E, Mak A, Malhotra A, Matouk C, Falcone G, Torres-Lopez V, Aneja S, Duncan J, Sansing L, Sheth K, Payabvash S. Deep learning for prediction of post-thrombectomy outcomes based on admission CT angiography in large vessel occlusion stroke. Frontiers In Artificial Intelligence 2024, 7: 1369702. PMID: 39149161, PMCID: PMC11324606, DOI: 10.3389/frai.2024.1369702.Peer-Reviewed Original ResearchEnd-to-endComputed tomography angiographyLarge vessel occlusionConvolutional neural networkDeep learning pipelineTrain separate modelsLogistic regression modelsResNet-50Deep learningAdmission computed tomography angiographyNeural networkLearning pipelineAdmission CT angiographyPreprocessing stepDiagnosis of large vessel occlusionsLarge vessel occlusion strokeReceiver operating characteristic areaEnsemble modelAutomated modelPre-existing morbidityCT angiographyReperfusion successNeurological examCross-validationOcclusion strokeBridging the gap: improving correspondence between low-field and high-field magnetic resonance images in young people
Cooper R, Hayes R, Corcoran M, Sheth K, Arnold T, Stein J, Glahn D, Jalbrzikowski M. Bridging the gap: improving correspondence between low-field and high-field magnetic resonance images in young people. Frontiers In Neurology 2024, 15: 1339223. PMID: 38585353, PMCID: PMC10995930, DOI: 10.3389/fneur.2024.1339223.Peer-Reviewed Original ResearchSuper-resolution approachLow fieldsConvolutional neural networkSuper-resolution methodsImage qualityLow image qualityImage correspondencesNeural networkProcessing imagesLow-field imagesHigh-field systemsStandard imagesLow-field MR systemImproved correspondenceLow-field systemSurface areaImagesSingle pairWhite matter volumeMR systemSubcortical volumesMR technologyGlobal mean cortical thicknessCortical thicknessCortical volume