Furen Xiao 89bb1e6331 Add visual QA script for TV label warping and registration methods ... - Implemented `qa_label_interpolation.py` to evaluate the registration of T1c and CT images using various methods (rigid, affine, and SyN). - The script generates warped TV images, visualizations, and summary metrics for each registration method. - Outputs include PNG figures for visual comparison, a summary JSON file with metrics, and cached registration transforms. - Added functionality for volume preservation checks and detailed logging of processing steps.		2026-10-04 08:32:56 +08:00
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common.py	feat(registration): align CT to T1c and add benchmarking	2026-09-28 16:20:30 +08:00
dataset.py	feat(train): implement checkpointing and robust data loading	2026-09-26 03:44:12 +08:00
impact_loss.py	refactor(impact): replace KonfAI pip runtime with Docker elastix_impact image	2026-09-30 21:23:18 +08:00
losses.py	feat: initial project structure	2026-09-25 16:00:37 +08:00
registration_pipelines.py	Add visual QA script for TV label warping and registration methods	2026-10-04 08:32:56 +08:00
training.py	feat(train): implement checkpointing and robust data loading	2026-09-26 03:44:12 +08:00
unet3d.py	feat: initial project structure	2026-09-25 16:00:37 +08:00