AI and Computer Vision: Transforming Cancer Care Through Collaborative Research

Medical images hold a wealth of information that is often underutilized in clinical decision-making. At the University of Utah, a multidisciplinary team spanning Pathology, Radiology, and Computer Science is harnessing artificial intelligence and computer vision to unlock that potential. One major research direction led by Professor of Pathology Beatrice Knudsen focuses on the development of computational tissue biomarkers. The larger team is creating multi-modal algorithms that integrate histopathology, radiology, and other clinical data to extract imaging biomarkers capable of improving cancer diagnosis, refining prognostic assessments, and guiding personalized treatment decisions for cancer patients.

This collaborative effort is meeting the needs of a diverse research team and driving significant progress. The group has secured two Department of Defense grants, an NIH R21 grant, and a collaborative catalyst team science award. Their work is being published in leading journals, and the first graduate student with dual advisors from this initiative will graduate this semester.

“These algorithms have the potential to assist clinicians in managing patients more effectively,” Professor Knudsen explains. “By combining expertise across disciplines, we are creating tools that make cancer care more precise and personalized.”

Dr. Beatrice Knudsen, Professor of Pathology & Dr. Allison Payne, Professor of Radiology

The project involves faculty, students, and staff from multiple departments, including Pathology, Radiology, Surgery, the Eye Institute, NICU, School of Dentistry, and ARUP Laboratories. For more details, see the team’s publications in PubMed.

Contributors: Beatrice Knudsen, Tolga Tasdizen, Shireen Elhabian, Allison Payne, and numerous clinical collaborators.

For more information, contact: beatrice.knudsen@path.utah.edu