Deprecated. See new version at https://github.com/zizhaozhang/distill2
This is the implementation for the Oral paper titled "TandemNet: Distilling Knowledge from Medical Images Using Diagnostic Reports as Optional Semantic References", Zizhao Zhang et al, in MICCAI 2017. Please find more details in the paper.
The code is written in Torch7. Install necessary libraries:
- Torch [https://github.com/torch/distro]
- Torch-gnuplot [https://github.com/torch/gnuplot]
- Torch-image [https://github.com/torch/image]
- Torch-display [https://github.com/szym/display]
- Lua-cjson [https://www.kyne.com.au/~mark/software/lua-cjson-manual.html]
TandemNet takes images and corresponding text (diagnosic reports) as inputs in order to train. You need to write your own DataLoader.lua. An example with detailed explanations has been provided in utils/DataLoader.lua.
sh scripts/train.sh
sh scripts/eval.sh
All results will be organized and saved in the folders inside checkpoints/tandemnet.
@inproceedings{Zhang2017TandemNet,
title={TandemNet: Distilling Knowledge from Medical Images Using Diagnostic Reports as
Optional Semantic References},
author={Zhang, Zizhao and Chen, Pingjun and Sapkota, Manish and Yang, Lin},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)},
year={2017}
}