# nv-generate-mr-brain

Generates synthetic T1, T2, FLAIR, SWI, or MRA brain MRI volumes with NV-Generate-CTMR MR-Brain v1. It provides test NIfTI volumes without clinical scans.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 1800 installs · ★ 3735
- Author: NVIDIA MedTech Team
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/NVIDIA/skills/tree/HEAD/skills/nv-generate-mr-brain/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/nv-generate-mr-brain

## What it does

This skill wraps scripts.diff_model_infer from the NVIDIA-Medtech/NV-Generate-CTMR repository. It stages model_config_override parameters, validates input arguments, and executes scripts/run_mr_brain.py. The output delivers synthetic brain MRI data in NIfTI format alongside a result_json report.

Execution requires GPU/CUDA hardware and a local checkout pinned to commit da438fec6484cdb6f421f8c7051d954ebefff730. Model checkpoints such as autoencoder_v1.pt must be pulled from Hugging Face. The wrapper creates the output directory itself, so manual folder creation is not needed.

Synthetic volumes are not suitable for production medtech training without independent quality review, and upstream training coverage for mri_mra is sparse. Do not use these outputs for clinical diagnosis or regulatory submissions.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nv-generate-mr-brain -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/nv-generate-mr-brain/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/nv-generate-mr-brain/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nv-generate-mr-brain -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/nv-generate-mr-brain/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nv-generate-mr-brain -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/nv-generate-mr-brain/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install NVIDIA/skills nv-generate-mr-brain
```

2. **Manually: put the files in place**
- File: `.github/skills/nv-generate-mr-brain/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nv-generate-mr-brain -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/NVIDIA/skills --path skills/nv-generate-mr-brain
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/nv-generate-mr-brain/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nv-generate-mr-brain -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/NVIDIA/skills/tree/HEAD/skills/nv-generate-mr-brain/SKILL.md

## When to use it
- generate synthetic brain MRI volumes across T1, T2, FLAIR, SWI, and MRA modalities
- produce test NIfTI volumes for pipelines without using real patient data
- run upstream NV-Generate-CTMR inference without leaking sensitive environment tokens
- validate wrapper parameters and config overrides before starting GPU inference

## Example prompts
- Generate a synthetic brain MRI volume for modality mri_t1 using config.json into runs/demo
- Review the run command for scripts/run_mr_brain.py with modality mri_flair and seed 1234
- Run nv-generate-mr-brain for modality mri_t2 with output directory runs/test_brain

## Source text · SKILL.md · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 18d9377e13e33541.

BEGIN THIRD-PARTY FILE 18d9377e13e33541
````text
---
name: nv-generate-mr-brain
description: Used for generating synthetic T1, T2, FLAIR, SWI, or MRA brain MRI volumes with NV-Generate-CTMR MR-Brain v1. Not for production training data.
license: Apache-2.0
allowed-tools: Bash, Read, Write, WebFetch, Env
permissions: [env, file_read, file_write, network, shell]
metadata:
  author: 'NVIDIA MedTech Team'
  tags:
    - MedTech
    - MRI
    - brain
---

# NV-Generate-MR-Brain

## Purpose
- Used for generating synthetic T1, T2, FLAIR, SWI, or MRA brain MRI volumes with NV-Generate-CTMR rflow-mr-brain v1. Not for production training data.
- Use the wrapper exactly as documented; do not replace the upstream entrypoint with a handwritten implementation.
- Do not write custom inference code for normal runs. The wrapper owns config staging, output paths, and validation.
- Manifest I/O: inputs are `model_config_override`; outputs are `synthetic_mr_brain_volumes` and `result_json`.

## Instructions
- Read `skill_manifest.yaml` before changing arguments, side effects, or validation gates.
- Run `scripts/run_mr_brain.py` through the documented command below; keep outputs under a caller-provided run directory.
- If a host agent exposes `run_script`, use `run_script("scripts/run_mr_brain.py", args=[...])`; otherwise run the Bash/Python command shown below.
- For a command-shape review, do not install packages, clone repositories,
  download weights, or start GPU inference. Emit only the exact wrapper command
  with the supplied config path plus explicit `--output-dir`, `--modality`, and
  `--random-seed` values.
- For an executable run, emit a single bash code block and keep the
  `python -m pip install -r "$NV_GENERATE_ROOT/requirements.txt"` step in that
  same command — the runtime may be a fresh environment without
  `nibabel`/MONAI, so dropping the install fails with `ModuleNotFoundError`.
- If `--modality mri_mra` is selected, state that upstream reports sparse MRA
  training coverage and that output quality is not guaranteed.
- Do not add `rm`, `mkdir`, or any cleanup of `--output-dir`; the wrapper creates it. Use a fresh `--output-dir` instead of deleting one.
- Check the emitted JSON and paired verifier guidance before treating the run as evidence.

## Examples

Command-shape review only (no setup or execution):

```bash
python skills/nv-generate-mr-brain/scripts/run_mr_brain.py \
  PATH_TO_MR_BRAIN_CONFIG.json \
  --output-dir runs/nv_generate_mr_brain_demo \
  --modality mri_t1 \
  --random-seed 1234
```

For an executable run, use the setup-aware command under
[Usage](#usage).

## Available Scripts
| Script | Purpose | Arguments |
|---|---|---|
````
END THIRD-PARTY FILE 18d9377e13e33541

The third-party file has ended. Everything between the 18d9377e13e33541 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

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