TransFusionNet: Liver tumor and vessel segmentation

TransFusionNet: Semantic and Spatial Features Fusion Framework for Liver Tumor and Vessel Segmentation Under JetsonTX2

Requirement

Package                Version
---------------------- ---------------
albumentations         0.5.2
imbalanced-learn       0.8.1
ml-collections         0.1.0
numpy                  1.20.3
opencv-python          4.5.4.58
pandas                 1.3.4
pynrrd                 0.4.2
scikit-image           0.18.3
scikit-learn           1.0.1
scipy                  1.7.2
seaborn                0.11.2
SimpleITK              2.1.1
torch                  1.8.0
tqdm                   4.62.3
vtk                    9.1.0

Train module

python trainTFNet.py

Citation

If you find this work useful for your research, please cite our paper

@ARTICLE{9893911,
  author={Wang, Xun and Zhang, Xudong and Wang, Gan and Zhang, Ying and Shi, Xin and Dai, Huanhuan and Liu, Min and Wang, Zixuan and Meng, Xiangyu},
  journal={IEEE Journal of Biomedical and Health Informatics}, 
  title={TransFusionNet: Semantic and Spatial Features Fusion Framework for Liver Tumor and Vessel Segmentation Under JetsonTX2}, 
  year={2022},
  volume={},
  number={},
  pages={1-12},
  doi={10.1109/JBHI.2022.3207233}}