King’s and NVIDIA researchers used Cambridge-1 to scale the models to the necessary size using multiple GPUs, and then applied a process known as hyperparameter tuning, which dramatically improved the accuracy of the models. Without Cambridge-1, the AI models would have taken months versus weeks to train and the resulting image quality would not have been as clear.
The use of synthetic data has the additional benefit that it can ensure patient privacy since the images were generated and it will allow King’s to open the research to the broader UK healthcare community. The aim of developing the AI models is to help diagnose neurological diseases based on brain MRI scans, but it may also be used to predict diseases that a brain may develop over time and enable preventative treatment. The AI models were developed by King’s and NVIDIA data scientists and engineers as part of The London Medical Imaging & AI Centre for Value Based Healthcare research funded by UK Research and Innovation and a Wellcome Flagship Programme (in collaboration with University College London). These models can help scientists understand what a human brain looks like across a variety of ages, genders, and diseases.
The Synthetic Brain Project is focused on building deep learning models that can synthesize artificial 3D MRI images of human brains.
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