Known as Project InnerEye, this is a collaboration between Microsoft Research, Cambridge University Hospitals NHS Foundation Trust (CUH), and the University of Cambridge.
Winning first prize for “Best Use of AI”, the Project InnerEye Deep Learning Toolkit is the result of eight years’ work developing machine learning to analyse patient scans to speed up preparation for radiotherapy treatment.
It is now being used as a research tool to help cancer patients in Cambridge, as Dr Raj Jena, radiotherapy consultant at CUH, explains: “Starting radiotherapy promptly improves cancer survival rates and reduces anxiety in newly diagnosed patients. But before any radiotherapy can take place, the oncologist must spend a significant amount of time – maybe one or two hours per patient – making sure the radiation will be delivered to the correct part of the body without damaging any healthy tissue.
“Our research shows that the InnerEye technology can potentially carry out this preparation as well as an expert clinician in just a few minutes.”
Microsoft Research recently made the Project InnerEye Deep Learning Toolkit available as open source, to help researchers and clinicians use the power of deep learning to help with the growing demand on healthcare, and to assist with the delivery of precision medicine for better patient outcomes.
Image: Consultant oncologist Dr Raj Jena explains how machine learning tool Project InnerEye will help speed up cancer waiting times