SASSnet

Code for paper: Shape-aware Semi-supervised 3D Semantic Segmentation for Medical Images(MICCAI 2020)

Our code is origin from UA-MT

You can find paper in Arxiv.

Usage

1. Clone the repo:

   git clone https://github.com/kleinzcy/SASSnet.git 
   cd SASSnet

2. Put the data in data/2018LA_Seg_Training Set.

3. Train the model

   cd code
   # for 16 label
   python train_gan_sdfloss.py --gpu 0 --label 16 --consistency 0.01 --exp model_name
   # for 8 label
   python train_gan_sdfloss.py --gpu 0 --label 8 --consistency 0.015 --exp model_name

Params are the best setting in our experiment.

4. Test the model

   python test_LA.py --model model_name --gpu 0 --iter 6000

   Our best model are saved in model dir.

Citation

If you find our work is useful for you, please cite us.