Lightning Talk: How DeepInverse Is Solving Imaging in Science and Healthcare With PyTorch - Andrew Wang, DeepInverse; Minh Hai Nguyen, Université de Toulouse
Deep learning has revolutionised imaging, a foundation of science and healthcare. DeepInverse is the PyTorch library for solving imaging problems, unifying deep learning methods (e.g. diffusion models), physics (medical, optics) and modern tooling. In this talk, we’ll show how the PyTorch community can get involved in this exciting yet accessible application of open-source AI.
AI methods in imaging must model the imaging physics, leading to interesting engineering problems e.g. efficient differentiable ops, physics-informed losses. We’ll show notebooks on real use-cases: accelerating brain MRI, reducing radiation in CT scans, imaging black holes.
PyTorch enthusiasts at any level/background can contribute - from training infra for scientific data to high-level generative modelling frameworks - their AI engineering skills can directly impact imaging across multiple fields.
DeepInverse is supported by a growing international user community and proudly rooted in Paris. We’ve joined the PyTorch Ecosystem and received the Prix Science Ouverte in 2024. We’re excited to join the PyTorch Conf to celebrate the vibrant French developer community!