The goal of this project is to train an accurate 3D Neural Network for Glioblastoma Tumor Segmentation using a limited dataset. To this end, we make use of Patch-Learning. Our work combines the BraTS21 winning U-Net design : Optimized U-Net for Brain Tumor Segmentation and the BraTS20 winning learning approach : nnU-Net for Brain Tumor Segmentation.
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Jawher-Ben-Abdallah/Glioblastoma_3D_Segmentation
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Glioblastoma 3D Segmentation with nnU-Net and Patch Learning.
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