An Automated Deep Learning Pipeline for EMVI and Response Prediction of Rectal Cancer Using Baseline MRI
Paper Link: https://www.nature.com/articles/s41698-024-00516-x
in your favourite virtual environment:
pip install -r requirements.txt
Firstly, you have to run a nnunet link: https://github.com/MIC-DKFZ/nnUNet/tree/nnunetv1
Then, extract stage features (you can use multifeature_extractor.py)
Then, you need to have a csv file where you have your classification fold information and id. Also, you need to have a label csv file where you store your targeted labels
Also, you can finetune hyperparameters in the config file
Then you can Train with the following command:
CUDA_VISIBLE_DEVICES=0 python trainer.py --load_json config/nnunet.json
TEST with:
CUDA_VISIBLE_DEVICES=0 python eval_test.py