A computer scientist at UCF has created software to help doctors locate white fat tissues in the body, allowing them to start treatment faster and more accurately.

Ulas Bagci, an assistant professor for the Center for Research in Computer Vision in the College of Engineering & Computer Science, started research for his software after learning about brown fat cells and their benefits, according to a release.

The software can also differentiate between brown — or good — fat cells that are beneficial in fighting off weight gain and can potentially slow cancer growth and that of white fat tissues. Additionally, it can determine whether the white fat tissues live just below the skin in subcutaneous cells or deeper in the visceral cells, potentially wrapping around organs.

"One immediate use of brown fat identification in the body is that a safe treatment for obesity can be suggested if the numbers or the activity of brown fat cells could be increased," Bagci said. "Considering that the obesity is a big struggle in the nation, activating brown fat in the body, or injecting brown fat cells to obese subjects can help them to fight obesity naturally."

Currently, the software is called QuanFat, but Bagci said that may change after UCF files the patents.The software takes about a minute to read results from PET and CT scans and gives doctors a more complete analysis than the images alone because the computer vision techniques can analyze the images much better than the human eye. It also works with markers, such as contrast dyes, that can lead to an even more accurate understanding of the disease extent, severity and cause, according to the release.

QuanFat took two years to research and eight months to develop, said Bagci, who's giving the software to hospitals for free as a resource for second opinions while UCF starts the process of patenting the software.

"Health information technology is not really willing to deeply support open-source software," Bagci said. "We would like to change this by providing accurate, efficient and robust software, which can be used in all hospitals and help clinicians to conduct their diagnostic and routine task with great help by the software."

Bagci and his team, computer science students Sarfaraz Hussein and Arjun Watane, are working to program the software to be compatible with MRI machines.

Bagci predicts that MRI machines will replace the clinical standard CT machine in fat quantification, sparing patients from being subjected to radiation from the CT machine.


Amelia Truong is a Digital Producer for the Central Florida Future. Follow her on Twitter at @Ameliatruong or email her at

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