MetaPlanner

---

MetaPlanner is an open source automated treatment planning method that performs meta-optimization of treatment planning hyperparameters. It is meant for educational/research purposes and supports planning in MatRad using one of their experimental branches.

If you find this project useful, please cite our work:

@misc{huang2021metaoptimization,
      title={Meta-optimization for Fully Automated Radiation Therapy Treatment Planning}, 
      author={Charles Huang and Yusuke Nomura and Yong Yang and Lei Xing},
      year={2021},
      eprint={2110.10733},
      archivePrefix={arXiv},
      primaryClass={physics.med-ph}
}

---

All source code for MetaPlanner and MatRad are provided under the terms of the GNU GENERAL PUBLIC LICENSE Version 3 (GPL v3). The precompiled mex files of the Ipopt optimizer in object code version are licensed under the Eclipse Public License Version 1.0 (EPL v1.0).

---

Basic Examples:

Begin by storing your CT dicoms and RtSt dicoms into the following structure:

.
├── /head_and_neck_src
│   ├── /head_and_neck_data/                    
│   ├──   ├── /CT/                    
│   ├──   ├── /RTst/
├── /prostate_src
│   ├── /prostate_data/                    
│   ├──   ├── /CT/                    
│   ├──   ├── /RTst/
└── ...

To run automated planning, simply modify and run this script for head and neck data, or this script for prostate data.

---

Environment

Please setup the environment using either (1) the yml file or (2) the copy here. If you choose to use (2), please follow the conda unpack instructions below:

# Unpack environment into directory `my_env`
$ mkdir -p my_env
$ tar -xzf my_env.tar.gz -C my_env

# Use Python without activating or fixing the prefixes. Most Python
# libraries will work fine, but things that require prefix cleanups
# will fail.
$ ./my_env/bin/python

# Activate the environment. This adds `my_env/bin` to your path
$ source my_env/bin/activate

# Run Python from in the environment
(my_env) $ python

# Cleanup prefixes from in the active environment.
# Note that this command can also be run without activating the environment
# as long as some version of Python is already installed on the machine.
(my_env) $ conda-unpack