Doctors may soon have help in the fight against cancer thanks to the University of Central Florida’s Computer Vision Research Center.
Engineers at the center have taught a computer how to detect tiny specks of lung cancer in CT scans, which radiologists often have a difficult time identifying. The artificial intelligence system is about 95 percent accurate, compared to 65 percent when done by human eyes, the team said.
“We used the brain as a model to create our system,” said Rodney LaLonde, a doctoral candidate and captain of UCF’s hockey team. “You know how connections between neurons in the brain strengthen during development and learn? We used that blueprint, if you will, to help our system understand how to look for patterns in the CT scans and teach itself how to find these tiny tumors.”
The approach is similar to the algorithms that facial-recognition software uses. It scans thousands of faces looking for a particular pattern to find its match.
Engineering Assistant Professor Ulas Bagci leads the group of researchers in the center that focuses on AI with potential medical applications.
The group fed more than 1,000 CT scans — provided by the National Institutes of Health through a collaboration with the Mayo Clinic — into the software they developed to help the computer learn to look for the tumors.
Graduate students working on the project had to teach the computer different things to…
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This article was originally posted on ScienceDaily.com.
