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Full body segmentation (all 104 structures) · mkurman | DecimalAI

scienceby mkurman

Full body segmentation (all 104 structures)

mkurman/total-segmentator

Source mkurman/zorai ↗License MIT

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.

SkillScore86Maintained

Automatic

Clinical / Healthcare pack

Last verified 8/21/2026

What it changes

Passed 19 of 22 test cases with the skill, and 11 of 22 without it.

Without skill50%

With skill86%

Checks it passed that the model alone missed

The command specifies -ta ribs
The response specifies -ta organ
The command specifies -ta vertebra

and 4 more in the full report

8 fixed11 passed either way3 still failing0 broke

Pass-rate lift: +36 pp
Tokens: -29%
Agent turns: 0%
Response time: -38%

Model gemini-3.6-flashMeasured 8/21/2026v119 of 22 cases passed with skill

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/mkurman-total-segmentator/SKILL.md https://app.decimal.ai/s/mkurman-total-segmentator/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add mkurman-total-segmentator, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/mkurman-total-segmentator/ and pins it in .decimal/skills.lock

decimalai skills add mkurman-total-segmentator

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/mkurman-total-segmentator/SKILL.md https://app.decimal.ai/s/mkurman-total-segmentator/SKILL.md

Raw file: /s/mkurman-total-segmentator/SKILL.md ↗ · machine-readable summary at /s/mkurman-total-segmentator.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 8

Prompt

I want to isolate only rib segmentations from `chest_ct.nii.gz` to `ribs_only.nii.gz` using TotalSegmentator CLI. What exact CLI invocation should be executed?

What was checked, without and with the skill
Checked	Without skill	With skill
The response includes -ta ribs in the TotalSegmentator command	Missed	Passed

case-22 · gemini-3.6-flash · 8/21/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md38 linessingle file

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

uv pip install TotalSegmentator

CLI Usage

# 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

from totalsegmentator.python_api import totalsegmentator

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

Workflow

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

Track record

Benchmark

19 / 22

test cases passed, vs 11 / 22 without

Adoption

Users: 1
Times used: 16

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

mkurman / zorai

skills/scientific-skills/total-segmentator/SKILL.md

View on GitHub ↗

License MITImported 8/3/2026Version v1

More skills from the same source and nearby in the registry, with their headline benchmark lift.