Furen Xiao
16b9828d15
- 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. |
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| .. | ||
| 01_build_ntuh_manifest.py | ||
| 02_build_m6_dataset.py | ||
| 03_scan_lee_t1c.py | ||
| 04_reconstruct_lee.py | ||
| 05_build_splits.py | ||
| 06_pseudo_label.py | ||
| 07_train.py | ||
| 08_eval.py | ||
| 09_run_iterative.py | ||
| bench_registration.py | ||
| benchmark_pipelines.py | ||
| make_screenshots.py | ||
| preprocess.py | ||
| scan_procs.py | ||
| test_dataloader.py | ||