More details are presented in the following papers, Video, and Slides:
If you find our work is useful in your research, please consider citing:
(1) Usformer: A Light Neural Network for Left Atrium Segmentation of 3D LGE MRI
@inproceedings{lin2023usformer,
title={Usformer: A Light Neural Network for Left Atrium Segmentation of 3D LGE MRI},
author={Lin, Hui and Tapia, Santiago Lopez and Schiffers, Florian and Wu, Yunan and Yang, Huili and Iakovlev, Nikolay and Allen, Bradley D and Avery, Ryan and Lee, Daniel C and Kim, Daniel and others},
booktitle={2023 31st European Signal Processing Conference (EUSIPCO)},
pages={995--999},
year={2023},
organization={IEEE}
}
(2) Usformer: A Small Network for Left Atrium Segmentation of 3D LGE MRI
@article{lin2024usformer,
title={Usformer: A Small Network for Left Atrium Segmentation of 3D LGE MRI},
author={Lin, Hui and L{\'o}pez-Tapia, Santiago and Schiffers, Florian and Wu, Yunan and Gunasekaran, Suvai and Hwang, Julia and Bishara, Dima and Kholmovski, Eugene and Elbaz, Mohammed and Passman, Rod S and others},
journal={Heliyon},
publisher={Elsevier}
}
To obtain the 2018 Atria Segmentation challenge dataset
- [Installation]
git clone https://github.com/HuiLin0220/Usformer.git
cd Usformer
pip install -e.
-
Usformer's architecture, plan, and weight (Google drive).
-
[Test]
Challenge dataset's configuration plan
python ./test.py
A case with median performance in terms of Dice scores in the challenge dataset.
Green lines: prediction
Red lines: groundtruth
Yellow: slice index
More results in two datasets: challenge dataset NU dataset
Usformer is developed on the nnU-Net framework. The Left Atrium Segmentation project is funded by the American Heart Association and the National Institutes of Health. Any questions, please email [email protected]