This repo is the official implementation for: Learning with Explicit Shape Priors for Medical Image Segmentation
BraTS 2020: Multimodal Brain Tumor Segmentation Challenge 2020
VerSe'19: Large Scale Vertebrae Segmentation Challenge
Automated Cardiac Diagnosis Challenge (ACDC)
We follow the z-score normalization strategy in nnUNet to preprocess the BraTS 2020, VerSe'19 and ACDC dataset.
- python 3.7
- pytorch 1.8.0
- torchvision 0.9.0
- simpleitk 2.0.2
- monai 0.9.0
If you want to train the model from scratch, run the training script as following.
python BraTS_train.py
python VerSe_train.py
python ACDC_train.py
If you want to test the model, run the testing script as following.
python BraTS_test.py
python VerSe_test.py
python ACDC_test.py
If you use our code or models in your work or find it is helpful, please cite the corresponding paper:
@article{you2023learning,
title={Learning with Explicit Shape Priors for Medical Image Segmentation},
author={You, Xin and He, Junjun and Yang, Jie and Gu, Yun},
journal={arXiv preprint arXiv:2303.17967},
year={2023}
}