並行醫學物理模擬

Nvidia introduced the Medical Physics Simulation framework as an open-source addition to its Isaac for Healthcare platform, helping surgical and diagnostic robots learn through embodied experience. The framework combines classical physics solvers with generative simulation to recreate the contact, force and soft-tissue interactions robots would normally encounter during real procedures.

The system pairs deterministic mechanics, such as catheter movement and tissue resistance, with Cosmos-H Dreams, a generative component that models visual and anatomical variation. Nvidia Warp and Newton enable thousands of parallel training environments, allowing developers to generate rare procedural edge cases on demand. Early adopters include CMR Surgical, Johnson & Johnson MedTech and Medtronic, which are contributing data or developing digital twins for urology, endovascular and catheter-navigation research.

For clinicians and device teams, the framework could accelerate embodied training, dataset generation and pre-hardware development. Its open-source design also allows auditors to inspect modelling assumptions, although real-world validation remains essential before clinical deployment.