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nv-generate-mr-brain-finetune

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Used for finetuning NV-Generate-CTMR MR-Brain v1 for T1, T2, FLAIR, SWI, or MRA data from a NIfTI datalist. Not for clinical or production data approval.

When to use

• Used for finetuning the NV-Generate-CTMR `rflow-mr-brain` v1 diffusion UNet from user-supplied T1, T2, FLAIR, SWI, or MRA NIfTI training volumes.
• Not for clinical interpretation, regulatory use, or approving synthetic data for production training.
• The wrapper stages the config glue locally and delegates execution to existing upstream scripts: `scripts.diff_model_create_training_data`, `scripts.diff_model_train`, and optionally `scripts.diff_model_infer`. It does not execute the note…
• Manifest I/O: inputs are `datalist` and `data_base_dir`; outputs are `finetuned_checkpoint`, optional `inference_outputs`, and `result_json`.
• The underlying training contract is the upstream config/env JSON (the same one driven from cell `[10]` of `train_diff_unet_tutorial.ipynb`). The wrapper stages those JSON files for you and exposes the most-tuned fields as CLI flags; the se…

When not to use

• Requires a current upstream `NV-Generate-CTMR` checkout with the existing diffusion training scripts. The skill itself stages the required config and datalist glue locally and does not depend on the notebook or PR #33.
• Full training can be expensive and is not deterministic across hardware, CUDA, and package versions.
• The wrapper gates file accounting and command provenance, not anatomical realism or downstream model utility.
• Not for clinical deployment, clinical interpretation, autonomous diagnosis, regulatory submission, or production training-data approval.

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