Foundation models for 3D medical image segmentation, synthetic data generation, clinical reasoning, and physical AI.
3 models built on Cosmos and GR00T for vision-language-action control, surgical world modeling, and sim-to-real transfer via Isaac and Holoscan
Healthcare Physical AI VLA
Vision-language-action model for multi-embodiment surgical and clinical robot control across 16 platforms.
Surgical World Model
Predict future surgical states and transfer simulation to photorealistic video for scalable synthetic data generation.
8 models spanning MONAI-powered segmentation, raw signal reconstruction, synthetic volume generation, and clinical VLM reasoning across CT, MRI, X-ray, and ultrasound
132-Class CT Segmentation
Automatic and interactive segmentation of 132 anatomical structures in CT images with point-click refinement.
345+ Class CT & MRI Segmentation
Automatic segmentation of 345+ anatomical structures across CT body, MRI body, and MRI brain modalities.
Raw MRI Signal Reconstruction
Transform raw MRI signals into high-quality clinical images with accelerated reconstruction and motion correction.
Raw Ultrasound Processing
Translate raw ultrasound pressure measurements into clinical-quality images with physics-informed AI.
3D CT Synthesis
Generate high-resolution synthetic CT volumes up to 512x512x768 with controllable anatomy and paired segmentation masks.
3D MRI Synthesis
Generate synthetic MRI volumes with Rectified Flow for 33x faster inference. Brain, abdomen, breast, and prostate coverage.
3D Brain MRI Synthesis
Generate synthetic brain MRI across T1w, T2w, FLAIR, and SWI contrasts with cross-sequence synthesis via ControlNet.
Built for medical imaging researchers and developers
Foundation models pre-trained on large-scale medical datasets. Fine-tune on your data instead of training from scratch.
CT, MRI, X-ray, ultrasound, and surgical video in one collection. Static images through dynamic physiology.
Create synthetic volumes to augment training, simulate rare pathologies, and enable privacy-preserving data sharing across institutions.
Download from HuggingFace and run locally. No API keys, no cloud dependency. Apache 2.0 source code with model weights for commercial and research use.
Built on MONAI for medical imaging, Cosmos for world models, and Isaac for physical AI. Composable configs, reproducible pipelines.
Every model includes pre-trained weights, example configs, and documentation. Go from paper to inference with minimal setup.