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.

What You Need To Know

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

  • A team of UW scientists have developed new medical technology
  • The MRI machine-learning network uses an algorithm to help surgeons visualize bleeding on the brain and help them safely remove it
  • In less than a minute, the network can provide a colored image of the bleeding location and quantify how much doctors should remove without risking re-injury

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.

“My task would be to identify the location of the intracerebral hemorrhage and segment both the clot and the edema surrounding the clot, and then move on to every single layer of that image,” Henningsen said.

Henningsen spent more than 100 hours gathering data for this new research on brain bleeds. He said he was excited and grateful for the opportunity to be part of this collaboration.

The UW-trained bioengineer and football player said he hopes this project can eventually support and improve something his football profession fears: traumatic brain injury.

“You can’t diagnose concussion with an MRI currently,” he said. “But I mean, maybe in the future, if you’re able to, you can use machine-learning to potentially detect certain abnormalities that the human eye couldn’t necessarily detect or things of that sort. Maybe we could get somewhere.”

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