# nv-generate-mr

Generates synthetic body MRI volumes using NV-Generate-CTMR rflow-mr. Useful for staging T1 MRI volume synthesis without paired segmentations.

- 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/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/nv-generate-mr

## What it does

The skill wraps the diffusion pipeline from `NVIDIA-Medtech/NV-Generate-CTMR`. It executes the primary entrypoint `scripts/run_mr.py`, sets up configuration overrides, runs `scripts.diff_model_infer` for the `rflow-mr` checkpoint, and writes the output NIfTI volume with a JSON summary.

Execution requires an NVIDIA GPU with at least 16 GB VRAM because the upstream codebase provides no CPU fallback. The environment also requires installing dependencies from the upstream `requirements.txt` and downloading `rflow-mr` weights before running inference.

The tool produces image-only synthetic body MRI volumes (such as `mri_t1`) without segmentation masks. It is not intended for brain MRI synthesis, and the upstream weights carry an NVIDIA Non-Commercial license restricting direct production training and clinical deployment.

## Install

### Claude Code (native platform)

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

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

### Codex

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

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

### Cursor

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

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

### GitHub Copilot

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

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

### Gemini CLI

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

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

### Windsurf (Devin Desktop)

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

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nv-generate-mr -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/SKILL.md

## When to use it
- generate synthetic 3D body MRI volumes from a JSON config
- run rflow-mr diffusion inference with fixed random seeds
- export synthetic T1 MRI data in NIfTI format with a run report
- stage configuration overrides and output directories for CTMR inference

## Example prompts
- Run nv-generate-mr with config runs/config.json into directory runs/out using modality mri_t1
- Execute scripts/run_mr.py for model_config.json with --random-seed 0 and save output to runs/nv_generate_mr_demo

## 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: 47468a323777fd2f.

BEGIN THIRD-PARTY FILE 47468a323777fd2f
```text
---
name: nv-generate-mr
description: Used for generating synthetic body MRI volumes with NV-Generate-CTMR rflow-mr. Not for paired masks or production training data.
license: Apache-2.0
allowed-tools: Bash
metadata:
  author: NVIDIA MedTech Team
  tags:
    - MedTech
    - MRI
    - generation
---

# NV-Generate-MR

## Purpose
- Used for generating synthetic body MRI volumes with NV-Generate-CTMR rflow-mr. Not for paired masks or 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_volumes` and `result_json`.

## Instructions
- Read `skill_manifest.yaml` before changing arguments, side effects, or validation gates.
- Run `scripts/run_mr.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.py", args=[...])`; otherwise run the Bash/Python command shown below.
- 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`.
- 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.

## Available Scripts
| Script | Purpose | Arguments |
|---|---|---|
| `scripts/run_mr.py` | Primary entrypoint declared by skill_manifest.yaml. | `MODEL_CONFIG.json --output-dir OUT_DIR --modality mri_t1 [--random-seed N] [--yes]` |

## Prerequisites
- Runtime requirements: GPU/CUDA when declared by the manifest; Python packages listed in `runtime.side_effects.pip_packages`.
- Side effects: writes generated outputs under the caller's `--output-dir`, may cache model assets under `~/.cache/huggingface/`, and may contact `https://huggingface.co` or `https://github.com` during setup.
- Run commands from the repository root unless an existing section below says otherwise.

## Limitations
- This is a thin wrapper. Inference, sampling, and decoding are delegated entirely to NVIDIA-Medtech/NV-Generate-CTMR's `scripts.diff_model_infer`. Do not modify code under $NV_GENERATE_ROOT or the repo-local fallback at .workbench_data/upstreams/NV-Generate-CTMR.
- rflow-mr generates image-only synthetic MRI volumes. It does not emit paired segmentation masks.
- The upstream README recommends `rflow-mr-brain` instead for brain MRI synthesis; use `skills/nv-generate-mr-brain` for that path.
```
END THIRD-PARTY FILE 47468a323777fd2f

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