# Content Based Image Retrieval

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This project explores the idea of using image retrieval, instead of end-to-end methods, to perform dose predictions. Given a new patient (query), we perform the task of retrieving treatment plans for similar patients from a database. The dose distribution of those retrieved patients can then be utilized in subsequent automated planning.

If you find this project useful, please cite our [work](https://arxiv.org/abs/2206.02912):
```
@misc{https://doi.org/10.48550/arxiv.2206.02912,
  doi = {10.48550/ARXIV.2206.02912},
  url = {https://arxiv.org/abs/2206.02912},
  author = {Huang, Charles and Vasudevan, Varun and Pastor-Serrano, Oscar and Islam, Md Tauhidul and Nomura, Yusuke and Yang, Yong and Xing, Lei},
  keywords = {Computer Vision and Pattern Recognition (cs.CV), Medical Physics (physics.med-ph), FOS: Computer and information sciences, FOS: Computer and information sciences, FOS: Physical sciences, FOS: Physical sciences},
  title = {Learning Treatment Plan Representations for Content Based Image Retrieval},
  publisher = {arXiv},
  year = {2022},
  copyright = {arXiv.org perpetual, non-exclusive license}
}

```
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All source code for this project is provided under the terms of the GNU GENERAL PUBLIC LICENSE Version 3 (GPL v3). 
