Model description

Proposed in the paper: UNETR: Transformers for 3D Medical Image Segmentation

UNEt TRansformers (UNETR) utilize a transformer as the encoder to learn sequence representations of the input volume and effectively capture the global multi-scale information, while also following the successful "U-shaped" network design for the encoder and decoder. The transformer encoder is directly connected to a decoder via skip connections at different resolutions to compute the final semantic segmentation output.

Open source status

• The model implementation is available
• The model weights are available

Provide useful links for the implementation

Model Implementation: https://github.com/Project-MONAI/research-contributions/tree/master/UNETR

Pretrained Model: https://drive.google.com/file/d/1kR5QuRAuooYcTNLMnMj80Z9IgSs8jtLO/view?usp=sharing (Based on BTCV dataset)