- 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.
- Added `--clip-ct LO HI` argument to clip CT intensities before registration and scoring, improving A/B comparisons.
- Implemented `_clip_image` function to handle intensity clipping of images.
- Updated registration functions to utilize CT clipping where beneficial, specifically in `register_niftyreg` and `register_synthmorph`.
- Enhanced `fixed_moving` function to ensure CT is always treated as the fixed image.
- Introduced Docker support for NiftyReg v2.1.1, including a Dockerfile for building the image.
- Updated documentation and help messages to reflect new features and usage instructions.
- Adjusted evaluation criteria for registration quality to account for intensity clipping.
Replace the conda-forge-dependent Elastix CLI path with the pip-installable
ITK-Elastix Python components so the benchmark can run elastix in the main
environment. Add SimpleITK/ITK image and transform conversion helpers, and
use the elastix 5.x EulerTransform rigid pipeline with Mattes MI and ASGD.
Update REGISTRATION_BENCHMARK.md and bench_registration.py documentation to
reflect the new elastix availability, results, and multi-environment merge
workflow. Ignore local elastix output directories in .gitignore.
- Updated regex patterns for improved matching of series names and tags.
- Added functionality to reject non-head series based on study and series descriptions.
- Implemented max voxel spacing check to filter out series with excessive spacing.
- Enhanced the reconstruction script to handle dynamic-frame series exclusions and artifact pruning.
- Modified output paths for reconstructed NIfTI files and added QA screenshot generation.
- Improved argument parsing in benchmark and pseudo-labeling scripts for better flexibility.
- Introduced a new script for generating QA screenshots from reconstructed volumes.
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.
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.
