Learning with Privileged Multimodal Knowledge for Unimodal Segmentation

Tensorflow implementation of our privileged multimodal knowledge learning framework.

Paper

Learning with Privileged Multimodal Knowledge for Unimodal Segmentation TMI 2021

Installation

• Install TensorFlow 1.10 and CUDA 9.0
• Clone this repo

git clone https://github.com/cchen-cc/PMKL
cd PMKL

Data Preparation

• Use nii2tfrecord function in ./preprocessing.py to convert nii data into tfrecord format to be decoded by ./data_loader.py

Train

• Specify the data path in ./main.py
• Run ./main.py to start the training process

Evaluate

• Specify the model path and data path in ./evaluate.py
• Run ./evaluate.py to start the evaluation.

Citation

If you find the code useful for your research, please consider cite our paper.

@article{chen2021learning,
  title={Learning with Privileged Multimodal Knowledge for Unimodal Segmentation},
  author={Chen, Cheng and Dou, Qi and Jin, Yueming and Liu, Quande and Heng, Pheng Ann},
  journal={IEEE Transactions on Medical Imaging},
  year={2021},
  publisher={IEEE}
}

Note

• Contact: Cheng Chen ([email protected])