CTSegmentation

MOOSE CT

MOOSE CT does automatic CT segmentation one body system at a time: organs, heart chambers and large vessels, the five lung lobes, each rib and vertebra, limb bones, trunk and hip muscles, or skeletal muscle, subcutaneous fat and visceral fat for body-composition research.

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

You upload
CT scan
You get
Outlined structures
Tasks
10
Cost per million voxels
€0.006

Is it right for your scan?

Intended use

Outlining groups of tissues on routine clinical CT for research, for example whole-body measurements or PET/CT analysis.

Known limitations

Tuned to routine clinical CT. Less accurate on unusual scan protocols, strong artefacts and scans of children.

Available tasks (10)

Organs

Default

Abdominal and thoracic organs: adrenal glands, bladder, brain, gallbladder, kidneys, liver, lung lobes, pancreas, spleen, stomach, thyroid lobes, trachea.

Body outline

Coarse body partitioning: legs, trunk, head, arms.

Peripheral bones

Limb and skull bones: carpals, clavicles, femur, fibula, fingers, humerus, metacarpals, metatarsals, patella, radius, scapula, skull, tarsals, tibia, toes, ulna.

Body composition

Skeletal muscle, subcutaneous fat and visceral fat, outlined in 3D over the whole scan.

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
Lalith Kumar Shiyam Sundar and colleagues, Quantitative Imaging and Medical Physics team, Medical University of Vienna, Austria. Nalvera.AI runs their published model and is independent of the authors.
Version
3.1.5 · Apache-2.0 · released 21 May 2025
Training data
MOOSE 3.0 clinical models (ENHANCE-PET / Shiyam Sundar et al.), trained on multi-centre clinical CT (and PET/CT) cohorts with expert-reviewed labels across digestive, lung, rib, peripheral-bone and other tissue groups. Adult human anatomy.

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.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.NV-Segment-CTCT · (Interactive) SegmentationNVIDIA’s CT segmentation model: 117 organs, bones, vessels, and muscles in one pass, plus tasks for the airway and the liver vessels.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: MOOSE CT v3.1.5. Accessed YYYY-MM-DD}
}
Research use only — not a medical device. Outputs are not validated for clinical diagnosis or treatment.
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