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Artificial intelligence techniques show potential in advancing image reconstruction, image quality, computer-aid diagnosis, and image-guided surgery. However, according to Yan, deep learning adversaries remain an obstacle in the widespread application, resulting in confusing image results and inaccuracy.
“The adversary might cause the system to generate undesired or unwanted outputs,” Yan said. “The clinicians may be confused by the output of the system, or a wrong diagnosis may just slip through. It could cause significant medical errors in the diagnosis process and cause significant cost to our health care system.”
Currently, some tools can protect algorithms against adversaries. However, the tools will often decrease the quality of algorithmic performance. According to the press release, the goal of the research is to protect the algorithm by developing artificial intelligence techniques that can guard against deep learning glitches without diminishing the quality and performance of the algorithm.
The tool created by Yan and his team will be able to detect adversarial images, correct errors, and improve the quality of information produced by the AI system. However, Yan explained that new algorithms created by the team must consider the overall system, not just the individual parts,to ensure that accuracy is not sacrificed as efficiency increases.
“This CAREER Award is a recognition of Professor Yan’s innovative research with broad applications to multiple areas,” said Deepak Vashishth, the director of CBIS. “For example, he and his team continue to advance the potential of AI to improve human health, while tackling persistent challenges that must be overcome along the way.”
“We envision such systems will help to make health care imaging more robust, more accurate, and will also boost the confidence of the users — especially the medical professionals,” Yan said.
By protecting algorithms, artificial intelligence technology will better serve the public by producing accurate results and improving care.
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