CTSegmentation

NV-Segment-CT

NV-Segment-CT is NVIDIA's segmentation model for CT scans. It outlines 117 organs, bones, vessels, and muscles automatically, with separate tasks for the airway and the liver vessels. In the Interactive Studio it outlines one structure from your clicks.

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Use NV-Segment-CT in your browser: it runs in the cloud. No coding, no installation.

You upload

CT scan

You get

Outlined structures

Tasks

Cost per million voxels

€0.006

Is it right for your scan?

Intended use

Outlining anatomy on CT scans for research: measuring organs and other structures across groups of patients, or a first draft that you then correct by hand.

Known limitations

CT scans only. Each scan is read at 1.5 mm resolution, so very small structures come out coarse. The liver vessels need a contrast-enhanced scan: without contrast the task finds little or nothing.

Available tasks (3)

Whole body

Default

117 structures: abdominal organs, the heart and major vessels, the lung lobes, every vertebra and rib, other bones, the spinal cord and the trunk and hip muscles.

Airway

The airway as one structure.

Liver vessels

The blood vessels inside the liver as one structure. Needs a contrast-enhanced scan (portal venous phase).

After the AI task

Correct the result in your browser, then measure each structure and follow it across your study. See what is measured

Research details

Built by

NVIDIA (Yufan He and colleagues), who published it as VISTA3D. Nalvera.AI runs their published model and is independent of the authors.

Version

0.6.0 · NVIDIA Open Model License · released 1 Apr 2026

Training data

Trained by NVIDIA on 11,454 CT scans covering 127 kinds of structures and several kinds of lesions (He et al., CVPR 2025).

Citations & references

Other models

Nalvera iSegCT / MRI · Interactive segmentationNalvera’s in-house model for interactive CT and MRI segmentation. Define the structures you need and refine their outlines directly in your browser.MAISI-v2CT / MRI · GenerationGenerate synthetic CT or brain MRI images without an input scan. Choose the image size and anatomy for research dataset creation.MerlinCT · Report generation · AnalysisExplore abdominal CT scans through generated research reports and predicted findings. Includes tasks for estimating five-year disease risk.MOOSE CTCT · SegmentationFocused CT segmentation for heart chambers, lung lobes, muscles, and other anatomical regions.MRSegmentatorMRI / CT · SegmentationSegment 40 organs, vessels, bones, and muscles from the chest to the hips on MRI or CT, with a body composition task for fat and abdominal muscles on MRI.MuscleMap MRIMRI · SegmentationSegment muscles and bones on whole-body MRI scans across different MRI contrasts, with coverage from the neck through the trunk to the legs.NV-Reason-CTCT · Report generationWrite structured chest or abdominal CT reports, or a step-by-step reasoning walkthrough that states its observations and uncertainty.TotalSegmentator CTCT · SegmentationWhole-body and regional CT segmentation, with additional tasks for individual organs, bones, muscles, and vessels.TotalSegmentator MRIMRI · SegmentationSegment organs, bones, vessels, and muscles on MRI scans. Choose whole-body segmentation or dedicated tasks for the body, spine, or liver.

Citing Nalvera.AI

Please cite the platform alongside the model's own paper.

@misc{nalvera,
  title        = {Nalvera.AI: a cloud platform for medical-imaging AI},
  author       = {{van der Heyden, Brent}},
  year         = {2026},
  howpublished = {\url{https://nalvera.ai}},
  note         = {Model: NV-Segment-CT v0.6.0. Accessed YYYY-MM-DD}
}

Research use only — not a medical device. Outputs are not validated for clinical diagnosis or treatment.

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