UW scientists and Denver Broncos player team up for new MRI machine-learning network project

By Kathryn Larson, Spectrum News 1

MADISON, Wis. — University of Wisconsin-Madison researchers said they were proud to publish a groundbreaking paper on a new MRI machine-learning network.

They determined how brightly colored scans can help surgeons recognize, and accurately remove, an intracerebral hemorrhage (ICH), or bleeding in the brain.

Walter Block, a professor of medical physics and biomedical engineering, leads the research team that developed a special algorithm to support doctors who must act quickly and with precision to extract a brain bleed.

“The trick is to visualize it and quantify it so that the surgeon has the information they need,” Block said.

Tom Lilieholm — a PhD candidate and lead author of the research — created the specific algorithm for the new color-coded MRI machine-learning network.

“We got pretty high accurate segmentations out of the machine here, 96% accurate clot, 81% accurate edema,” he said, showing off one of the study’s MRI slides.

Lilieholm said it can show a surgeon in less than a minute just how much of the hemorrhage they can safely remove.

“It’s really kind of useful to have that, and to have robust data to compare against,” Lilieholm said. “That’s where Matt kind of came in.”

The “Matt” Lilieholm was referring to is NFL player Matt Henningsen.

Henningsen is from Menomonee Falls. Before becoming a Denver Bronco, he attended UW-Madison, where he excelled on the football field and in the classroom. He earned a bachelor’s and master’s degree from the university. Read more…