- Implemented 09_run_iterative.py for MONAI to orchestrate iterative pseudo-labeling rounds, including training, predicting, and evaluation.
- Created 01_prepare_dataset.py, 02_plan_preprocess.py, 06_pseudo_label.py, 07_train.py, 08_eval.py, and 09_run_iterative.py for nnU-Net to manage dataset preparation, planning, training, evaluation, and iterative pseudo-labeling.
- Enhanced error handling and logging throughout the scripts for better traceability.
- Added functionality to handle negative pseudo-labels and TTA options during inference.
- Included visualization of Dice scores across rounds for both MONAI and nnU-Net.
Update README.md to include detailed project overview, environment
requirements, data sources, and a comprehensive directory layout.
Add nnU-Net pipeline documentation and directory descriptions.
Update .gitignore to exclude nnU-Net specific directories and add
new scripts directory for nnU-Net pipeline.
Add initial nnU-Net pipeline scripts.
