README.md

# ADAM
**Disclaimer**: We are not the host of the data.
Please make sure to read the requirements and usage policies of the data and **give credit to the authors of the dataset**!

Please read the information from the homepage carefully and follow the rules and instructions provided by the original authors when using the data.
- Homepage: http://adam.isi.uu.nl/
- Subtask: Task 1

## Setup
0. Follow the installation instructions of nnDetection and create a data directory name `Task019FG_ADAM`. We added FG to the ID to indicate that unruptered and ruptured aneurysms are treated as one i.e. we are running a foreground vs background detection without distinguishing the classes.
1. Follow the instructions and usage policies to download the data and place the data into `Task019FG_ADAM / raw / ADAM_release_subjs`
2. Run `python prepare.py` in `projects / Task019_ADAM / scripts` of the nnDetection repository.
3. Run `python split.py` in `projects / Task019_ADAM / scripts` of the nnDetection repository.
4. [Info]: The provided instructions will automatically create a patient stratified random split. We used a random split for our challenge submission. By renaming the provided split file in the `preprocessed` folders, nnDetection will automatically create a random split.

The data is now converted to the correct format and the instructions from the nnDetection README can be used to train the networks.