Working out how to zap a tumor with radiation is a laborious process for physicians. Google’s machine-learning division, DeepMind, thinks AI can help ease the burden.
When medics apply radiotherapy to a cancer patient, they have to carefully determine which parts of the body should be exposed to radiation in order to kill the tumor while ensuring that as much healthy surrounding tissue as possible is preserved. The process, known as segmentation, requires the doctor to manually draw areas that can and can’t be treated onto a 3-D scan of the patient’s tumor site. The process is particularly complex for head and neck cancers, in which the tumor often sits immediately next to many important anatomical features.
Now, though, DeepMind will work with University College Hospital in London to develop an artificial-intelligence system that can automate the process. DeepMind will analyze 700 anonymized scans from former patients who suffered from head and neck cancers. They hope to create an algorithm that can learn how physicians make decisions about this part of the treatment process, ultimately segmenting the scans automatically.