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This Github repository serves as the access point to the SPARK Academy MICCAI BraTS challenge models from groups participating in the 2023 SPARK Academy.
For more information about SPARK, the academy's objectives visit SPARK's event website. All training events are accessible to registered participants through SPARK's event website.
The Sprint AI Training for African Medical Imaging Knowledge Translation (SPARK) program is designed to train a new generation of African artificial intelligence (AI) experts in medical imaging who can train others. We use a case-based learning approach and collective intelligence from various related fields (radiology, medical physics, computer science, neurology/neurosurgery, and oncology) to rapidly turn AI knowledge into action.
Each SPARK Academy is aimed at a real-world use case and implements collective intelligence built around a networking space to advance AI capacity and rapid implementation in Africa. Our first SPARK Academy endorsed by The Medical Image Computing and Computer Assisted Intervention (MICCAI) Society trained 70 African clinicians and scientists to develop state-of-art AI methods for glioma brain tumor segmentation. The first program brought together students and clinicians from across 15 African- and 3 Southeast Asian countries to co-develop informed AI methods that will accurately segment brain tumors into sub-regions on magnetic resonance imaging (MRI) scans.