News

Updates and announcements from NVIDIA MedTech Open Models

Agent Skills

Run the models from your coding agent

We've published Medical AI Skills — agent-callable skills that let a coding agent (Claude Code, Cursor, or Codex) run these models correctly on the first try, from a plain-language prompt. Twelve skills now cover the imaging models:

  • Run skills — segmentation (NV-Segment-CT, NV-Segment-CTMR), synthetic generation (NV-Generate-CT, NV-Generate-MR, NV-Generate-MR-Brain), and chest-X-ray reasoning (NV-Reason-CXR)
  • Finetune skills — continual-learning and finetuning wrappers for NV-Segment-CT, NV-Generate-CT, and NV-Generate-MR-Brain
  • DICOM utilities — preflight, metadata extraction, and DICOM→NIfTI conversion

Install one with npx skills add NVIDIA-Medtech/medical-AI-skills, then ask your agent in plain language — each model page lists example prompts.

In a with-vs-without study across 9 model skills and 3 agent backends, agents with the skill produced a valid first-shot command 79/81 times versus 0/81 with the upstream README alone — an engineering-reproducibility result, not a clinical claim.

Skills follow the open Agent Skills spec; browse them on GitHub. Engineering and research use only — not a medical device.

GTC 2026

Physical AI and Expanded Imaging Models at GTC

We are releasing 6 new models at GTC 2026, expanding MedTech Open Models from 5 models to 11 models across medical imaging and physical AI.

Physical AI (new category)

  • GR00T-H — Vision-language-action model for multi-embodiment surgical and clinical robot control across 16 platforms
  • Cosmos-H-Surgical — Surgical world model for state prediction and sim-to-real photorealistic video transfer
  • Cosmos-H-Surgical-Simulator — Action-conditioned simulation for in-silico policy evaluation

New Imaging Models

  • NV-Raw2Insights-MRI — Raw MRI signal reconstruction with accelerated imaging and motion correction
  • NV-Raw2Insights-US — Physics-informed raw ultrasound-to-image processing
  • NV-Generate-MR-Brain — Multi-contrast brain MRI synthesis with ControlNet (T1w, T2w, FLAIR, SWI)

All models are available on the MedTech Open Models HuggingFace collection with code and documentation on GitHub.

Open Models Hub Released

We are pleased to announce the NVIDIA MedTech Open Models Hub: a collection of open foundation models for medical imaging that segment, reason, and generate across clinical data. Designed to accelerate research and development in medical AI.

Initial Models

  • NV-Segment — 3D CT and MR segmentation across 345+ anatomical regions with automatic detection and interactive point-click refinement
  • NV-Generate — High-resolution synthetic 3D CT and MR volume generation with anatomical annotations for privacy-preserving data augmentation
  • NV-Segment-CTMR — 345+ class automatic segmentation across CT body, MRI body, and MRI brain
  • NV-Generate-MR — Synthetic MRI with Rectified Flow for 33x faster inference (brain, abdomen, breast, prostate)
  • NV-Reason — Vision-language model with chain-of-thought reasoning for chest X-ray interpretation, aligned with radiologist analysis workflows

Model weights are distributed through the MedTech Open Models collection on HuggingFace. The stack is built with MONAI, the NVIDIA co-founded open-source toolkit for medical AI.