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Found 4 papers, 4 papers with code
Hybrid Window Attention Based Transformer Architecture for Brain Tumor Segmentation
As intensities of MRI volumes are inconsistent across institutes, it is essential to extract universal features of multi-modal MRIs to precisely segment brain tumors.
Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task
In this concept, the 3D segmentation network learns from dual reciprocal adversarial learning approaches.
A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation
We propose a Transformer architecture for volumetric segmentation, a challenging task that requires keeping a complex balance in encoding local and global spatial cues, and preserving information along all axes of the volume.
Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation
Segmentation of images is a long-standing challenge in medical AI.
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