# Total Segmentator

> Total Segmentator is an Agent Skill for documents published in the mkurman/zorai repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Tool for robust segmentation of 104+ anatomical structures in CT images. Uses nnUNet-based models for whole-body, organ, and bone segmentation. One-line CLI for comprehensive body-part segmentation.

- Skill name: `total-segmentator`
- Category: [Documents](https://www.openparable.com/skill/documents/1)
- Source: https://github.com/mkurman/zorai/blob/HEAD/skills/scientific-skills/total-segmentator/SKILL.md
- Repository: mkurman/zorai (320 GitHub stars when collected)

## SKILL.md

## Overview

TotalSegmentator segments 104+ anatomical structures in CT images using nnUNet-based models. Run full-body, organ, or bone segmentation with a single CLI command.

## Installation

```bash
uv pip install TotalSegmentator
```

## CLI Usage

```bash
# Full body segmentation (all 104 structures)
TotalSegmentator -i input_ct.nii.gz -o output_seg.nii.gz

# Organ-only segmentation (liver, kidneys, spleen, etc.)
TotalSegmentator -i input_ct.nii.gz -o organ_seg.nii.gz -ta organ

# Appendicular bones
TotalSegmentator -i input_ct.nii.gz -o bone_seg.nii.gz -ta appendicular_bones
```

## Python API

```python
from totalsegmentator.python_api import totalsegmentator

segmentation = totalsegmentator("input_ct.nii.gz", "output_seg.nii.gz")
```

## Workflow

1. Obtain CT scan in NIfTI format
2. Run `TotalSegmentator -i input.nii.gz -o output.nii.gz`
3. Task types: `total` (104 structures), `organ`, `vertebra`, `ribs`, `appendicular_bones`
4. Output is a multi-label segmentation mask
5. Extract volumes per label for quantitative analysis

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Source: https://www.openparable.com/skill/documents/total-segmentator (OpenParable). Cite the canonical URL above.