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.

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.

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

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)
  

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

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