UNETR
UNet Transformer
**UNETR**, or **UNet Transformer**, is a [Transformer](https://paperswithcode.com/methods/category/transformers)-based architecture for [medical image segmentation](https://paperswithcode.com/task/medical-image-segmentation) that utilizes a pure [transformer](https://paperswithcode.com/method/transformer) as the encoder to learn sequence representations of the input volume -- effectively capturing the global multi-scale information. The transformer encoder is directly connected to a decoder via [skip connections](https://paperswithcode.com/methods/category/skip-connections) at different resolutions like a [U-Net](https://paperswithcode.com/method/u-net) to compute the final semantic segmentation output.
UNETR: Transformers for 3D Medical Image Segmentation
https://paperswithcode.com/paper/unetr-transformers-for-3d-medical-image
UNETR: Transformers for 3D Medical Image Segmentation