2023
Detection of Intracerebral Hemorrhage Using Low-Field, Portable Magnetic Resonance Imaging in Patients With Stroke
Mazurek M, Parasuram N, Peng T, Beekman R, Yadlapalli V, Sorby-Adams A, Lalwani D, Zabinska J, Gilmore E, Petersen N, Falcone G, Sujijantarat N, Matouk C, Payabvash S, Sze G, Schiff S, Iglesias J, Rosen M, de Havenon A, Kimberly W, Sheth K. Detection of Intracerebral Hemorrhage Using Low-Field, Portable Magnetic Resonance Imaging in Patients With Stroke. Stroke 2023, 54: 2832-2841. PMID: 37795593, PMCID: PMC11103256, DOI: 10.1161/strokeaha.123.043146.Peer-Reviewed Original ResearchMeSH KeywordsCerebral HemorrhageHumansIschemic StrokeMagnetic Resonance ImagingStrokeTomography, X-Ray ComputedInfection diagnosis in hydrocephalus CT images: a domain enriched attention learning approach
Yu M, Peterson M, Cherukuri V, Hehnly C, Mbabazi-Kabachelor E, Mulondo R, Kaaya B, Broach J, Schiff S, Monga V. Infection diagnosis in hydrocephalus CT images: a domain enriched attention learning approach. Journal Of Neural Engineering 2023, 20: 10.1088/1741-2552/acd9ee. PMID: 37253355, PMCID: PMC11099590, DOI: 10.1088/1741-2552/acd9ee.Peer-Reviewed Original ResearchMeSH KeywordsAttentionChildDeep LearningHumansHydrocephalusNeural Networks, ComputerTomography, X-Ray Computed
2021
Assessing the utility of low resolution brain imaging: treatment of infant hydrocephalus
Harper JR, Cherukuri V, O’Reilly T, Yu M, Mbabazi-Kabachelor E, Mulando R, Sheth KN, Webb AG, Warf BC, Kulkarni AV, Monga V, Schiff SJ. Assessing the utility of low resolution brain imaging: treatment of infant hydrocephalus. NeuroImage Clinical 2021, 32: 102896. PMID: 34911199, PMCID: PMC8646178, DOI: 10.1016/j.nicl.2021.102896.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBrainChildDeep LearningHumansHydrocephalusImage Processing, Computer-AssistedRadiographic Image Interpretation, Computer-AssistedTomography, X-Ray ComputedConceptsDeep learning enhancementLow-quality imagesDeep learningQuality imagesDeep learning algorithmsEnhanced imageRole of machineLearning enhancementImage qualityLearning algorithmAcceptable image qualityReconstruction errorImage resolutionImagesAlgorithmCT imagesLearningCT counterpartsNoise ratioTreatment planningPlanningNew standardStructural errorsExperienced pediatric neurosurgeonsMachine
2017
Learning Based Segmentation of CT Brain Images: Application to Postoperative Hydrocephalic Scans
Cherukuri V, Ssenyonga P, Warf B, Kulkarni A, Monga V, Schiff S. Learning Based Segmentation of CT Brain Images: Application to Postoperative Hydrocephalic Scans. IEEE Transactions On Biomedical Engineering 2017, 65: 1871-1884. PMID: 29989926, PMCID: PMC6062853, DOI: 10.1109/tbme.2017.2783305.Peer-Reviewed Original ResearchAlgorithmsBrainHumansHydrocephalusImage Interpretation, Computer-AssistedInfantMachine LearningTomography, X-Ray Computed