BeU2-Net

The official implementation for the JBHI-2025 paper "Boundary-Enhanced U2-Net for Simultaneous Four-Chamber Segmentation in Transthoracic Echocardiography".

Datasets

Public datasets

• CAMUS：https://www.creatis.insa-lyon.fr/Challenge/camus/
• EchoNet-Dynamic：https://echonet.github.io/dynamic/

Private datasets

• Private A4C：contact us if you want to use this dataset mengyuanqin@stu.kust.edu.cn.

Getting Started

Install

first, download the project's code:

#clone the project
git clone 
cd project-name
conda create -n myenv python=3.8 -y
conda activate myenv

then, install all requirements:

pip install -r requirements.txt

prepare the dataset: modify the data_path in config_setting.py. The dataset for private dataset is as following organized:

├── [Your Data Path]
    ├── edges
    ├── images
    ├── masks
    └── label.csv

run train.py.

Citation

if you find this project useful, please consider citing:

@article{meng2025boundary,
  title={Boundary-Enhanced $ U\^{}$\{$2$\}$ $-Net for Simultaneous Four-Chamber Segmentation in Transthoracic Echocardiography},
  author={Meng, Yuanqin and Chai, Shengjie and Xiao, Haoyu and Meng, Zhaohui and Wang, Qingwang and Shen, Tao},
  journal={IEEE Journal of Biomedical and Health Informatics},
  year={2025},
  publisher={IEEE}
}