ScaleFormer

Code for IJCAI 2022 paper 'ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation'

1.Dataset

• Synapse:
  The dataset we used is provided by TransUnet's authors. Please go to link for details, or please send an Email to jienengchen01 AT gmail.com to request the preprocessed data. If you would like to use the preprocessed data, please use it for research purposes and do not redistribute it (following the TransUnet's License).

• Monuseg:
  The dataset we used is provided by UCTransNet's authors. Please go to link for details.

• ACDC:
  We will upload the dataset later.

2.Enviorments

• python 3.7
• pytorch 1.9.0
• torchvision 0.10.0 test.py

3.Reference

• TransUnet
• SwinUnet
• UcTransNet