The implementation of artificial intelligence in serial monitoring of post gamma knife vestibular schwannomas: A pilot study
Singh M, Jester N, Lorr S, Briano A, Schwartz N, Mahajan A, Chiang V, Tommasini S, Wiznia D, Buono F. The implementation of artificial intelligence in serial monitoring of post gamma knife vestibular schwannomas: A pilot study. Clinical Imaging 2025, 123: 110495. PMID: 40388858, DOI: 10.1016/j.clinimag.2025.110495.Peer-Reviewed Original ResearchConceptsGamma knife radiosurgeryVestibular schwannomaPost-GKSTumor growthVS volumeHalting tumor growthRetrospective cohort studyAssess treatment efficacyManual segmentationHearing lossBenign tumorsPaired t-testT1-weighted MRI scansAssess statistical significanceCohort studyDice similarity coefficientNeurological functionTreatment efficacyClinical monitoringMRI scansStatistical significancePercentage changeSchwannomaSpatial overlapTumorThe development of an artificial intelligence auto-segmentation tool for 3D volumetric analysis of vestibular schwannomas
Jester N, Singh M, Lorr S, Tommasini S, Wiznia D, Buono F. The development of an artificial intelligence auto-segmentation tool for 3D volumetric analysis of vestibular schwannomas. Scientific Reports 2025, 15: 5918. PMID: 39966622, PMCID: PMC11836447, DOI: 10.1038/s41598-025-88589-x.Peer-Reviewed Original ResearchConceptsGround-truth datasetDice scoreVestibular schwannomaImage processing accuracyVolumetric analysisML-based algorithmsMeasuring tumor sizeMean dice scoreAuto-segmentation toolAccurate AIAI modelsTumor sizeTumor modelVS tumorsTumor growthTesting stageAI-LTumorImage processing softwareClinical practicePatient recruitmentProcessing softwareSchwannomaDatasetManual segmentation
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