- Updated `05_monai_run_iterative.py` to include legacy mode and improved configuration options for training. - Introduced `UNetBAligned` class in `monai_common.py` for deep supervision and instance normalization. - Modified `train_transform` and `make_dataloader` in `monai_common.py` to support B-aligned data protocol with Z-score normalization and augmentation. - Added new loss functions `nn_dc_and_ce` and `b_dc_and_ce` in `losses.py` for improved training performance. - Enhanced `Unet3D` architecture in `unet3d.py` to support leaky ReLU and deep supervision. - Created new augmentation functions in `augment_b.py` for Pipeline B's training, including rotation, scaling, and noise. - Implemented new training scripts `run_b_100ep_stages.sh` and `run_c_bloss_100ep_after_b.sh` for structured training and evaluation. - Updated dataset handling in `dataset.py` to accommodate new augmentation and normalization strategies. |
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|---|---|---|
| .. | ||
| 01_monai_build_rows.py | ||
| 02_monai_train.py | ||
| 03_monai_pseudo_label.py | ||
| 04_monai_eval_test.py | ||
| 05_monai_run_iterative.py | ||
| monai_common.py | ||