MSR-UNet

CODE for MSR-UNet: An Effective Model for Multiscale Information and Long-Range Dependency in Medical Image Segmentation

This code is mainly based on the MISSFormer, at the following link: https://arxiv.org/abs/2109.07162

1. Environment

• Please prepare an environment with Ubuntu 20.04, with Python 3.6.13, PyTorch 1.8.0, and CUDA 11.1.1.

2. Train/Test

• Train

python train.py --dataset Synapse --root_path your DATA_DIR --max_epochs 400 --output_dir your OUT_DIR  --img_size 224 --base_lr 0.05 --batch_size 24

• Test

python test.py --dataset Synapse --is_savenii --volume_path your DATA_DIR --output_dir your OUT_DIR --max_epoch 400 --base_lr 0.05 --img_size 224 --batch_size 24

References

• TransUnet
• Swin-Unet
• MISSFormer

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Possible errors and solutions

If can not run, please try make a new folder under model_out, and named as predictions. or download the model from baidu disk, PIN: MSRU