by Faquan Chen, Jingjing Fei, Yaqi Chen, and Chenxi Huang*.
Official code for "Decoupled Consistency for Semi-supervised Medical Image Segmentation". (MICCAI 2023)
This repository is based on PyTorch 1.8.1, CUDA 10.1, and Python 3.6.13. All experiments in our paper were conducted on an NVIDIA GeForce RTX 1080ti GPU with an identical experimental setting.
We provide code, data_split, and models for PROMISE12 and ACDC datasets.
Data could be got at PROMISE12 and ACDC.
To train a model,
python train_dcnet_prostate.py #for Prostate training
python train_dcnet_acdc.py #for ACDC training
To test a model,
python test_prostate.py #for Prostate testing
python test_ACDC.py #for ACDC testing
Our code is adapted from MC-Net, SSNet, and SSL4MIS. Thanks to these authors for their valuable works and hope our model can promote the relevant research as well.
If you have any questions, welcome contact me at 'chenfaquan@stu.xmu.edu.cn'