An ensemble of nnU-Net, MedNeXt and SwinUNETR with radiomic-subtype-tuned post-processing achieves whole-tumor lesion-wise Dice of 0.926, 0.801 and 0.688 on the BraTS 2024 PED, MEN-RT and MET test sets.
Medical Image Analysis 43, 98–109 (2018)
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Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor Segmentation
An ensemble of nnU-Net, MedNeXt and SwinUNETR with radiomic-subtype-tuned post-processing achieves whole-tumor lesion-wise Dice of 0.926, 0.801 and 0.688 on the BraTS 2024 PED, MEN-RT and MET test sets.