AI-based autocontouring

Clinical AI tools built for radiation oncology

Fully automatic, browser-based, DICOM-native auto-contouring — backed by dedicated cloud GPUs. Upload a CT scan and receive complete 3D structures across every slice, with zero user input.

< 3 min
Head & Neck OARs
225+
structures supported
0
seed points required

Start here

The whole picture, one page at a time.

The challenge

Manual delineation is the slowest step in the planning pathway — and the one that varies most between clinicians, between sites, and between one long day and the next.

  • Hours of drawing per patient
  • Inter-observer variability
  • Contouring gates the whole queue
Read the challenge

Why ContourOAI

Everything conventional auto-contouring makes hard, done differently: browser-based instead of workstation-locked, fully automatic instead of seeded, your model instead of a shared one.

  • No TPS plugin, no vendor lock-in
  • Zero user input per scan
  • Institution-private custom models
See the comparison

How it works

From CT upload to ready-to-review RT Structs in five steps — inside the DICOM workflow you already have, with no new hardware and nothing for clinicians to install.

  • Upload, queue, infer, review, return
  • Batch mode: upload tonight, review in the morning
  • Head & neck OARs in under 3 minutes
See the full flow

Coverage

Validated across 225+ structures spanning ten model groups, with a further 92+ structures in active testing and validation.

  • Cranial, H&N, thorax, abdomen, pelvis, skeleton
  • 20 atlas-consistent nodal levels
  • DSC and volumetric metrics per structure
See everything covered

Trust & security

Anonymisation happens inside your network, before anything leaves it. A mandatory clinician review gate means no structure set reaches a plan unchecked.

  • On-premises DICOM gateway, TLS 1.3
  • Zero patient data retained post-inference
  • EU, Mumbai or Hyderabad data residency
Read the trust model

Questions clinical teams ask

Data residency, regulatory posture, TPS integration, what happens when a contour is wrong, and who owns a model trained on your cases.

  • Does patient data leave our network?
  • What stops an incorrect contour reaching a plan?
  • Can we run it fully air-gapped?
Read the FAQ

Contact us

Get in touch

Questions, demos, or account access — we'd love to hear from you. Access is restricted; contact us for an account.

support@orcrist.ai