Semi-supervised Learning for Generalizable Intracranial Hemorrhage Detection and Segmentation
Emily Lin, Esther L. Yuh
Abstract
To develop and evaluate a semi-supervised learning model for intracranial hemorrhage detection and segmentation on an out-of-distribution head CT evaluation set.
Topics & Concepts
Artificial intelligenceGeneralizability theoryReceiver operating characteristicSegmentationSørensen–Dice coefficientPixelMedicineNeuroradiologyData setSimilarity (geometry)Ranking (information retrieval)Pattern recognition (psychology)Computer scienceMachine learningImage segmentationMathematicsImage (mathematics)StatisticsNeurologyPsychiatryIntracerebral and Subarachnoid Hemorrhage ResearchAcute Ischemic Stroke ManagementBrain Tumor Detection and Classification