README.md

Official MCTSeg

This is the source code for the paper, "A Multimodal Feature Distillation with CNN-Transformer Network for Brain Tumor Segmentation with Incomplete Modalities", of which I am the first author.

Model

The model configuration (i.e., network construction) file is net.py in the directory .\model. To train and test by running train.py and test.py.

Recommended dependencies:

Python <= 3.8
Torch <= 1.7.1
CUDA <= 11.1

Evaluation

Datasets Brain Tumor Segmentation (BraTS) Challenge 2018/2020 (BraTS2018/BraTS2020).

Suggested Citation

Our manuscript has been uploaded on arXiv. Please cite our paper if you use code from this repository:

Plain Text

• IEEE Style
  M. Kang, F. F. Ting, R. C.-W. Phan, Z. Ge, and C.-M. Ting, "A multimodal feature distillation with cnn-transformer network for brain tumor segmentation with incomplete modalities," arXiv:2404.14019 [cs.CV], Apr. 2024.
  

• Nature Style
  Kang, M., Ting, F. F., Phan, R. C.-W., Ge, Z, & Ting, C.-M.. A multimodal feature distillation with CNN-Transformer network for brain tumor segmentation with incomplete modalities. Preprint at https://arxiv.org/abs/2404.14019 (2024).
  

• Springer Style
  Kang, M., Ting, F. F., Phan, R.C.-W., Ge, Z., Ting, C.-M.: A multimodal feature distillation with cnn-transformer network for brain tumor segmentation with incomplete modalities. arXiv preprint arXiv:2404.14019 (2024)
  

License

PKGSeg is released under the BSD 3-Clause "New" or "Revised" License. Please see the LICENSE file for more information.

Copyright Notice

Many utility codes of our project base on the codes of PyTorch-3DUNet, mmFormer, Vision Transformer PyTorch, and Factor-Transfer-pytorch repositories.