This repository includes the official project of TFCNs, presented in our paper: TFCNs: A CNN-Transformer Hybrid Network for Medical Image Segmentation
, which is accepted by ICANN 2022 (International Conference on Artificial Neural Networks).
paper link: https://arxiv.org/abs/2207.03450 or https://doi.org/10.1007/978-3-031-15937-4_65
Email: dihanli@stu.xmu.edu.cn
Please contact dihan or me if you need the further help.
model/ : save for the model you have train
networks/ : all the component that construct our TFCNs
preprocess.py : simple data augumentation
train_utils.py : some tools used for training
utils.py : some tools used for testing
you can run the train.py and test.py for training and testing.
Please prepare an environment with python=3.7, and then use the command "pip install -r requirements.txt" for the dependencies.
@inproceedings{li2022tfcns,
title={TFCNs: A CNN-Transformer Hybrid Network for Medical Image Segmentation},
author={Li, Zihan and Li, Dihan and Xu, Cangbai and Wang, Weice and Hong, Qingqi and Li, Qingde and Tian, Jie},
booktitle={International Conference on Artificial Neural Networks},
pages={781--792},
year={2022},
organization={Springer}
}