By Melanie Evans
Facial-recognition software correctly matched photos of research
volunteers to unidentified medical scans of their heads, in a new
study of images that are commonly used in brain research.
The finding draws attention to a privacy threat that will
increase with technology improvements and the growth of health-care
data, experts in medical imaging and facial recognition said.
Researchers at the Mayo Clinic used commercially available
facial-recognition software to match photographs of about 80
volunteers to unidentified MRI images that show outlines of the
head in addition to the brain itself. The software correctly
matched 83% of the images, they reported in the New England Journal
Results are the latest to find technology has outflanked privacy
protections in health care, where an aggressive push is under way
to amass and mine medical data from patient medical records,
research, medical devices and consumer technology such as
Information on the identities of participants is typically kept
separate from the data, to protect patients' privacy as databases
of information get shared. But other studies have identified people
from genetic information and data from wearable activity-monitoring
devices that had been stripped of personal information.
The findings suggest existing privacy protections don't go far
enough, the study's authors said. They also point to the continuing
challenge of anticipating new risks from emerging technology, as
well as to the need for caution in handling medical data, said I.
Glenn Cohen, director of Harvard University's Petrie-Flom Center
for Health Law Policy, Biotechnology and Bioethics. "Our
imaginations are only so good," he said.
Mayo Clinic researchers launched the study after noticing the
clarity of images used to look at brain structures in studies on
aging, Alzheimer's disease and dementia, said Christopher Schwarz,
a Mayo Clinic computer scientist and researcher, who works with the
images and is lead author of the study. "If that was my dad, could
I recognize him?" Mayo Clinic researchers speculated, Mr. Schwarz
The answer was likely yes, he said. That raised concerns about
privacy should algorithms be able to pick out faces on a much
greater scale. "How bad of a problem is this?" the researchers
Mayo Clinic recruited 84 volunteers, ages 34 to 89, who had
recently received an MRI, or magnetic resonance imaging, scan of
the head during a clinic study. Volunteers were photographed from
five angles. Researchers reconstructed an image of each face from
the MRIs, which capture the outline from skin, fat and bone marrow
in the skull but don't capture bone or hair.
The study then tested facial-recognition software from Microsoft
Azure to match an MRI-generated face reconstruction to its owner's
photo. The algorithm correctly matched 70 of 84 images, the study
said. For another 10 images, the software ranked the correct photo
in its top five candidates.
Microsoft declined to comment.
Results didn't totally surprise researchers, who themselves saw
distinct facial features in MRI images, Mr. Schwarz said.
Nonetheless, findings were sobering. "We found that this really is
a problem," he said.
Identifying an MRI used in research could expose private
information used in studies, such as family medical history,
illnesses, genetic data and risks for diseases, he said. Research
studies typically collect personal information from patients and
their medical records.
Mayo Clinic researchers hope to develop a fix to publish
broadly, Mr. Schwarz said. Alternatives on the market now, such as
blurring or removing some data from MRIs, can limit brain-image
quality, he said.
Privacy threats from MRIs are likely limited, however, and the
study's test of facial-recognition software avoided some harder
challenges found in everyday life, Mr. Schwarz and other
researchers who weren't involved in the study said.
"The risk to the typical patient is really small," said Eliot
Siegel, a radiology professor at the University of Maryland School
of Medicine, who has studied the issue but wasn't involved in the
Researchers typically pledge not to try to identify medical
study participants under data-sharing contracts, he said.
Facial-recognition software also likely wouldn't work as well when
searching for matches across thousands of random photos instead of
dozens of images.
Still, facial-recognition software continues to make significant
advancements in accuracy after a major leap from deep learning in
2014, experts in the technology said. Privacy risks are compounded
by rapidly growing amounts of medical data for valuable research,
experts in medical and facial-recognition technology said.
"As time goes on, that risk is going to increase and it's really
important to consider that as we continue to develop larger and
larger machine-learning databases," Dr. Siegel said.
Write to Melanie Evans at Melanie.Evans@wsj.com
(END) Dow Jones Newswires
October 23, 2019 17:17 ET (21:17 GMT)
Copyright (c) 2019 Dow Jones & Company, Inc.
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