Furen Xiao
e7721760f2
- 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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164 B
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15 lines
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164 B
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data
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runs/
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results/
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logs/
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nnu/
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runs_bench/
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runs_nnu/
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runs_monai/
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__pycache__/
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elastix/
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niftyreg/NiftyReg-Ubuntu-v2.1.1.zip
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niftyreg/NiftyReg-Ubuntu-v2.1.1/
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.kilo/ |