Developed at King’s College London in collaboration with University College London, the model and images have helped scientists better understand what the human brain looks like, supporting research to predict, diagnose and treat brain diseases including dementia, stroke, and multiple sclerosis.
The algorithm was created using the UK’s most powerful supercomputer - NVIDIA Cambridge-1 – which allowed researchers to train the AI in weeks rather than months and produce images of far higher quality.
According to King’s, the high-resolution 3D images have all the characteristics of real human brains, such as correct folding patterns and regions of the right size. It can also accurately produce images that reflect clinical factors like age, sex or disease status.
Data produced by the model was realistic enough to replicate human anatomy; the team showed that a dementia research study running on real data would show the same outcomes as a study running on generated synthetic data.
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By looking at large volumes of data, the AI model learned how age and sex affect the brain, and how pathologies impact anatomy. These tools have many direct uses, from making AI diagnosis more accurate and equitable to helping neuroscientists better understand how brains change with age and disease.
In a statement, Dr Jorge Cardoso, from King’s School of Biomedical Engineering & Imaging Sciences, said: “We've taught a computer what the human brain looks like. The potential for neurological research is enormous. With more development, the technology could help us understand which drugs are best for each patient, how certain conditions might evolve differently in different patients, and how a person’s brain might react to a specific treatment.
“Put simply, clinicians would be able to tailor and optimise treatment plans based on the model’s predictions for each specific patient.”
Parashkev Nachev, Professor of Neurology at UCL said: “To understand the imaged brain we must first acquire the power to recreate it. This implies not merely learning the appearance of a set of brains, but defining the bounds on the possible, counterfactual characteristics of any brain, in health and disease.
“It's a solution which paves the way to overcoming the greatest challenge in medicine: how to predict the optimal treatment for each individual patient to deliver truly personalised care.”
The research is also being expanded to other organs like the heart and lungs, as well as complex multi-system diseases like cancer.
The AI models were developed by King’s, UCL and NVIDIA data scientists and engineers, in collaboration with The London Medical Imaging & AI Centre for Value Based Healthcare, with the research funded by UK Research and Innovation, and the Wellcome Innovations-funded Programme for High-dimensional Translation in Neurology.
The research is detailed in Nature Machine Intelligence.
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