- 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.
Introduce the third segmentation pipeline using MONAI (1.6.x) to allow
direct comparison with Pipelines A and B. This includes the implementation
of the iterative pseudo-labeling workflow, training scripts, and
inference protocols.
- Add `scripts_monai/` directory containing the MONAI pipeline scripts.
- Update documentation in `README.md` and `AGENTS.md` to include MONAI
package requirements and pipeline details.
- Configure `.gitignore` to exclude MONAI-specific run directories.
- Update data directory descriptions to include MONAI pseudo-labels.
