Agent skill · AI & Agents

nii2dcm

Use this skill whenever the user wants to convert NIfTI files (.nii or .nii.gz) to DICOM format, create DICOM series from processed neuroimaging results, write segmentation/registration/analysis outputs back to DICOM for PACS compatibility or clinical viewer comparison, or transfer metadata from reference DICOM files. Triggers include: mentions of 'NIfTI to DICOM', 'nii to dcm', 'convert nii.gz to DICOM', 'dicomify segmentation', 'nii2dcm', 'bring results back to DICOM', 'create DICOM from NIfTI', 'nii to dicom series', or any request to take post-processed neuroimaging results (segmentation,

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill nii2dcm --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 6 KB
Bundled scripts: none
Requires: - claw-shell
Path: skills/neuroclaw/nii2dcm/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# NIfTI to DICOM conversion ## Overview A NIfTI file (.nii/.nii.gz) is a compact format widely used in neuroimaging research, typically stripped of patient metadata. DICOM is the clinical standard for medical images, including rich metadata and interoperability with PACS/hospital systems. This skill wraps `nii2dcm` (v0.1.6, May 2025) to convert NIfTI volumes into single-frame DICOM series (multi-slice 2D), primarily for MRI-derived data. It supports modality-specific metadata (MR, SVR) and optional metadata transfer from a reference DICOM file. **Research use only** — not certified for clinical diagnosis, treatment, or patient care. ## Quick Reference | Task | Approach / Command Flag | |-------------------------------|------------------------------------------| | Basic conversion (generic) | `nii2dcm input.nii.gz output_dir/` | | MRI multi-slice series | `--dicom-type MR` or `-d MR` | | SVR (3D swept volume recon) | `--dicom-type SVR` or `-d SVR` | | Copy patient/study metadata | `--ref-dicom ref.dcm` or `-r ref.dcm` | | Custom series description | Add via wrapper or post-process | | Verify output | Open in Horos, 3D Slicer, ITK-Snap | ## Installation ### Via pip (recommended for N

What's inside
Steps it walks through
  1. Overview
  2. Quick Reference
  3. Installation
  4. Via pip (recommended for NeuroClaw)
  5. From source (for customization / debugging)
  6. Usage Examples
  7. Create standard MRI DICOM series
  8. Create SVR (swept volume reconstruction) series
  9. Generic conversion (no modality metadata)
  10. With reference DICOM (copy patient/study metadata)
  11. NeuroClaw recommended wrapper (simpler for agent calling)
  12. Important Notes & Limitations
  13. When to Call This Skill
  14. Complementary / Related Skills
Commands it runs
pip install nii2dcm>=0.1.6
or latest
pip install git+https://github.com/tomaroberts/nii2dcm.git
git clone https://github.com/tomaroberts/nii2dcm.git
cd nii2dcm
python -m venv venv
source venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt
pip install .
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About this skill
What does the nii2dcm skill do?

Use this skill whenever the user wants to convert NIfTI files (.nii or .nii.gz) to DICOM format, create DICOM series from processed neuroimaging results, write segmentation/registration/analysis outputs back to DICOM for PACS compatibility or clinical viewer comparison, or transfer metadata from reference DICOM files. Triggers include: mentions of 'NIfTI to DICOM', 'nii to dcm', 'convert nii.gz to DICOM', 'dicomify segmentation', 'nii2dcm', 'bring results back to DICOM', 'create DICOM from NIfTI', 'nii to dicom series', or any request to take post-processed neuroimaging results (segmentation,

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill nii2dcm --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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