The Cambridge-1 supercomputer has been pivotal in this aim, because the previous biggest computers – albeit very substantial in computing power – could not scale to the AI model size needed to produce good quality data.
Data availability can be a major issue, but Cambridge-1 is helping to solve that via its massive computational power to generate the large synthetic datasets for research and algorithm development. Cambridge-1 is one of the world’s top 50 fastest supercomputers, built on 80 DGX A100 systems, integrating NVIDIA A100 GPUs, Bluefield-2 DPUs, and NVIDIA HDR InfiniBand networking. KCL researchers are leveraging NVIDIA hardware and the open-source MONAI software framework supported by Pytorch and NVIDIA’s software solutions like cuDNN and Omniverse for visualising brains in the Synthetic Brain Project. Dr Cardoso, who led the team and developed and trained the AI model, said a next step is to expand the process to other body parts and disease, and in a longitudinal progression.
With more than 12 years expertise in advanced image analysis, big data, and artificial intelligence, Dr Jorge Cardoso is senior lecturer in artificial medical intelligence at King’s College London, where he leads a research portfolio on big data analytics, quantitative radiology and value-based healthcare. He is also Chief Technology Officer of the new London Medical Imaging and AI Centre for Value-based Healthcare.
Source: Healthcare in Europe