How quantum-inspired algorithms could help doctors detect cancer earlier

– People think that quantum computing is something that’s way
off in the distance. So we primarily work on
magnetic resonance imaging, or MRIs. It’s a super powerful technique, but it’s expensive and it’s slow. We’re trying to solve
this optimization problem of how we should scan. What’s the best way to scan a patient that has this particular disease. That’s where the quantum
inspired optimization really will make a difference. We’re talking about gains of
ten, twenty, thirty percent, and maybe even factors
of two or three in speed. Those are hundreds of
thousands of patients a year that we can impact with just these gains that may sound kind of modest, but it can really have a
massive impact globally. Our group has been trying
to drive advances in speed and make it much more specific. We’re doing this through a method that we call magnetic
resonance fingerprinting, or MRF. This is a technology that allows us to really look at each part of the body and make a specific
diagnosis as to what’s there. The more sensitive we
can make that sequence, the earlier we’re gonna see those things. With fingerprinting, we
get a quantitative result for each and every pixel. We’re hoping that that allows us to get a really specific look inside that tissue to understand is that cancer
or is that normal tissue so that we can really guide
treatment in a reproducible way. The quantum inspired optimization is able to give us a better
result than we can get with any of the conventional
methods that we’ve seen.

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