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TotalSegmentator-KonfAI
VBoussot/TotalSegmentator-KonfAI
TotalSegmentator-KonfAI is a image segmentation model from VBoussot. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for konfai. The card lists the license as apache-2.0.
KonfAI-accelerated adaptation of TotalSegmentator — whole-body multi-organ CT / MRI segmentation, built with KonfAI.
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Public
Updated Sep 21, 2026
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At a glance
- Task
- Image Segmentation
- Library
- konfai
- License
- apache-2.0
- Access
- Public
- Created
- Nov 7, 2025
- Updated
- Sep 21, 2026
- SHA
- e1b363a2
Model card
From the Hugging Face model README
TotalSegmentator-KonfAI
KonfAI-accelerated adaptation of TotalSegmentator — whole-body multi-organ CT / MRI segmentation, built with KonfAI.
🧩 Models
| Task | Modality | Labels | Ensemble | Notes |
|---|---|---|---|---|
total | CT | 117 | 5 | full accuracy |
total-3mm | CT | 117 | 1 | fast (3 mm) |
total_mr | MRI | 50 | 2 | |
total_mr-3mm | MRI | 50 | 1 | fast (3 mm) |
3D residual UNet · patch [96, 128, 160] · resampled to 1.5 mm.
🚀 Usage
pip install totalsegmentator-konfai
totalsegmentator-konfai segment total -i input_ct.nii.gz -o output/
- Generic runner:
konfai-apps infer VBoussot/TotalSegmentator-KonfAI:total -i input_ct.nii.gz -o output/ - Interactive: SlicerKonfAI — the ⚙ Advanced dialog overrides patch size and batch size.
⚡ Performance & VRAM
Same input, same weights (Datasets 291–295, 1.5 mm, 5-model total), same PyTorch build (2.12.1, cu13.0), single NVIDIA RTX PRO 5000 (24 GB), TotalSegmentator 2.18.0. Peak RAM = process-tree resident set; peak VRAM = over baseline. Measured with KonfAI's benchmarks/perf/bench_apps.py (2026-09-09).
| Case (voxels) | Tool | Time | Peak RAM | Peak VRAM |
|---|---|---|---|---|
| S (240 × 220 × 200) | KonfAI | 7.6 s | 5.0 GB | 12.3 GB |
| Original | 29.9 s | 22.6 GB | 3.3 GB | |
| M (249 × 246 × 246) | KonfAI | 17.7 s | 5.2 GB | 15.4 GB |
| Original | 58.3 s | 25.2 GB | 7.1 GB | |
| L (512 × 512 × 531) | KonfAI | 212 s | 17.6 GB | 10.6 GB |
| Original | 377 s | 47.9 GB | 23.1 GB |
1.8–3.9× faster, 2.7–4.8× less host RAM. KonfAI trades more VRAM on small/medium cases (larger patches, GPU accumulation) for the speed-up while staying inside 24 GB; on large cases streaming bounds VRAM (10.6 GB) where the original nears the card limit (23.1 GB), so KonfAI is then lighter on both RAM and VRAM. The batch size is auto-selected from your free VRAM; on cards below 24 GB use total-3mm (1 model, 3 mm). Override with --patch-size / --batch-size.
🔗 Links
- 🧠 Original TotalSegmentator: github.com/wasserth/TotalSegmentator
- 🧠 KonfAI: github.com/vboussot/KonfAI
- 📦 PyPI: totalsegmentator-konfai
- Task
- Image Segmentation
- Library
- konfai
- License
- apache-2.0
- Created
- Nov 7, 2025
- Updated
- Sep 21, 2026