2024
P10.25.A STANDARDIZATION AND AUTOMATIZATION OF MEASURING AND REPORTING BRAIN METASTASIS OVER TIME BY LEVERAGING ARTIFICIAL INTELLIGENCE
Weiss D, Bousabarah K, Deuschl C, Chadha S, Ashraf N, Ramakrishnan D, Moawad A, Osenberg K, Schoenherr S, Lautenschlager J, Holler W, Westerhoff M, Schrickel E, Memon F, Moily N, Malhotra A, Lin M, Aboian M. P10.25.A STANDARDIZATION AND AUTOMATIZATION OF MEASURING AND REPORTING BRAIN METASTASIS OVER TIME BY LEVERAGING ARTIFICIAL INTELLIGENCE. Neuro-Oncology 2024, 26: v61-v61. PMCID: PMC11485790, DOI: 10.1093/neuonc/noae144.201.Peer-Reviewed Original ResearchReports of brain metastasesBrain metastasesInter-observer variabilityFollow-up imaging of patientsPost-Gamma knife radiosurgeryBrain tumorsRANO-BM criteriaFollow-up imagingBoard-certified neuroradiologistsTreatment response monitoringMean Dice coefficientImages of patientsNnU-Net segmentationManual diameter measurementsBM evaluationRANO-BMRetrospective studyTreatment regimenSpearman correlation coefficientInter-rater variabilityMRI reportsIdentified lesionsPercentual changePost-gammaNeuroradiologists
2022
NIMG-02. PACS-INTEGRATED AUTO-SEGMENTATION WORKFLOW FOR BRAIN METASTASES USING NNU-NET
Jekel L, Bousabarah K, Lin M, Merkaj S, Kaur M, Avesta A, Aneja S, Omuro A, Chiang V, Scheffler B, Aboian M. NIMG-02. PACS-INTEGRATED AUTO-SEGMENTATION WORKFLOW FOR BRAIN METASTASES USING NNU-NET. Neuro-Oncology 2022, 24: vii162-vii162. PMCID: PMC9661012, DOI: 10.1093/neuonc/noac209.622.Peer-Reviewed Original Research