DEDUPEDWhat do you want to do?
3 use cases
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Get organ masks from a CT or MR scan in one command
Run the default task to write one segmentation file per anatomical class.
View prompt
Using wasserth/TotalSegmentator, install it with `pip install TotalSegmentator`, run `TotalSegmentator -i ct.nii.gz -o segmentations` on <my scan>, and summarize which classes came out nonempty.
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Measure organ volumes and intensities automatically
Add the statistics flag so each segmented class comes with its volume and mean intensity.
View prompt
With wasserth/TotalSegmentator, run the total task on every scan in <my folder> with `--statistics`, then build one CSV of per organ volumes across the cohort.
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Find the right task and class names before you run
Use totalseg_info to print the available tasks and their classes without downloading weights.
View prompt
Using wasserth/TotalSegmentator, run `totalseg_info --json` and write me a small Python helper that picks the right task and `--roi_subset` names for <the structures I care about>.
What people are building with Total Segmentator
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Hands-onthe web
Built Anatomy Lab, a CT structure viewer, on TotalSegmentator masks
He ran TotalSegmentator 2.18.0 on the project's public test CT in total fast mode at 3 mm on Apple MPS, one run taking 58.9 seconds. Around the output he built Anatomy Lab, a viewer with 12 structures, three synchronized slice views, 3D and organ volumes, and notes the masks have not been reviewed by a clinician.
By Igor Kosolapov (kossolapov.com) on the web
Real builds shared on X, Hacker News, Reddit, DEV and GitHub, summed up by Deduped from each post and its links; each card links to the original post. See what people are building with other repos
Quick start with Total Segmentator
- Check you have what it needs: Python 3.10 or newer and PyTorch 2.0.0 or newer; A Nifti file, or a folder or zip of all DICOM slices of one patient, as input; A GPU for reasonable runtime; CPU works with the --fast or --roi_subset options.
- Open wasserth/TotalSegmentator on GitHub and read the README and license.
- Install it with
pip install TotalSegmentator - For CT run
TotalSegmentator -i ct.nii.gz -o segmentations - For MR run
TotalSegmentator -i mri.nii.gz -o segmentations --task total_mr - On CPU add
--fastor--roi_subset, and on an M series Mac use--device mps
These steps come from our top use case, Get organ masks from a CT or MR scan in one command, which also has a copy-paste agent prompt.
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Get them freeAbout this repo
- Who it is forMedical imaging researchers and engineers who need organ and structure masks from CT or MR scans.
- Why it is hot3.1k stars, picked up by one AI source we track
- Sourcegithub.com/wasserth/TotalSegmentator ยท Back to Hot repos
Requirements
- Python 3.10 or newer and PyTorch 2.0.0 or newer
- A Nifti file, or a folder or zip of all DICOM slices of one patient, as input
- A GPU for reasonable runtime; CPU works with the --fast or --roi_subset options
- A free non-commercial license number for the non-open tasks and for totalseg_get_body_stats
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Questions about Total Segmentator
What is Total Segmentator?
TotalSegmentator segments most major anatomical structures in any CT or MR image from the command line. The default total task covers 117 classes on CT and total_mr covers 50 on MR, with dozens of subtasks for vessels, head and neck, teeth, liver segments and more. Extra commands predict body stats, contrast phase and modality, and it can write per class volume statistics or DICOM output. It is an open-source project on GitHub: https://github.com/wasserth/TotalSegmentator.
How do I use Total Segmentator?
Install it with pip install TotalSegmentator; then For CT run TotalSegmentator -i ct.nii.gz -o segmentations; For MR run TotalSegmentator -i mri.nii.gz -o segmentations --task total_mr. The use cases on this page give the full steps and a copy-paste agent prompt for each job.
Who is Total Segmentator for?
Medical imaging researchers and engineers who need organ and structure masks from CT or MR scans.
What can I do with Total Segmentator?
3 use cases so far, for example: Get organ masks from a CT or MR scan in one command; Measure organ volumes and intensities automatically; Find the right task and class names before you run. Each has steps and a copy-paste agent prompt.
What do I need to run Total Segmentator?
Python 3.10 or newer and PyTorch 2.0.0 or newer; A Nifti file, or a folder or zip of all DICOM slices of one patient, as input; A GPU for reasonable runtime; CPU works with the --fast or --roi_subset options; A free non-commercial license number for the non-open tasks and for totalseg_get_body_stats.
What are alternatives to Total Segmentator?
Other hot AI repos in Security and science: Security Audit Skill, GPU Unlock, Syft, Esm, Alphafold3.
Is Total Segmentator safe to run?
Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.