Brain tumor segmentation with self-ensembled, deeply-supervised 3D U-net neural networks: a BraTS 2020 challenge solution

Understand

Brain tumor segmentation is a critical task for patient's disease management.

• In order to automate and standardize this task, we trained multiple U-net like neural networks, mainly with deep supervision and stochastic weight averaging, on the Multimodal Brain Tumor Segmentation Challenge (BraTS) 2020 training dataset.
• Two independent ensembles of models from two different training pipelines were trained, and each produced a brain tumor segmentation map.
• These two labelmaps per patient were then merged, taking into account the performance of each ensemble for specific tumor subregions.