Bioengineering Professors Earn Jump Arches Awards

9/30/2025 Lilli Bresnahan

Each year, the Jump ARCHES research program awards funding to support research involving clinicians, engineers and social scientists to develop technologies and devices that could revolutionize medical training and health care delivery. This year, research grants have been given to 14 projects, four of which included bioengineering faculty. This article features the projects from our department; a full list of projects is available on the Health Care Systems Engineering Site.

Written by Lilli Bresnahan

Each year, the Jump ARCHES research program awards funding to support research involving clinicians, engineers and social scientists to develop technologies and devices that could revolutionize medical training and health care delivery. 

This year, research grants have been given to 14 projects, four of which included bioengineering faculty. Below are the projects from our department; a full list of projects is available on the Health Care Systems Engineering Site.

Machine Learning 4D Heart Subsegmentation

Bioengineering professor at The Grainger College of Engineering Brad Sutton and Matthew Bramlet, MD, director of the Advanced Imaging and Modeling at OSF HealthCare, were rewarded funds for their research that aims to improve cardiac imaging by automating the segmentation of heart chambers in 3D and 4D models created from CT scans. Developed by the AIM Lab, the technology uses machine learning to help doctors receive more accurate heart measurements, making diagnosis faster and easier. By shifting from 2D to advanced 4D models, the project supports better care for complex conditions like congenital heart disease and reduces the workload for medical teams. 

VR Surgical Behavioral analysis Phase 1

Jennifer Amos, a bioengineering professor at Illinois Grainger Engineering and Matthew Bramlet, MD, director of the Advanced Imaging and Modeling at OSF, received funding for their research that uses virtual reality to help surgeons better plan complex congenital heart surgeries. By turning medical scans into 3D models and using machine learning to analyze the heart, the system allows for more precise, personalized planning for the patient. It also studies how expert and new surgeons make decisions, aiming to improve training, confidence and surgical outcomes.

Automating Aortic Aneurysm Analysis from Medical Imaging: A Phase II ARCHES

Bioengineering professor at University of Illinois Grainger Brad Sutton and Matthew Bramlet, MD, director of the Advanced Imaging and Modeling at OSF, secured funding for phase II of their research to expand the technology for automated 3D aortic sedimentation and measurement. This will improve the detection and monitoring of aortic aneurysms to automatically measure the aorta in 3D from CT and MRI scans. The new phase will expand the tool to work across different types of scans, helping doctors catch problems earlier, reduce errors and better identify patients at risk. 

Canine pre-clinical imaging models for neurological interventions in glioma

Kari Foss, assistant professor in The Department of Veterinary Clinical Medicine at the University of Illinois Urbana-Champaign, Andrew Tsung, director of neurological services at OSF HealthCare, Brad Sutton Illinois Grainger Engineering professor in bioengineering, Fan Lam, associate professor in bioengineering at Illinois Grainger Engineering and director of the MS in BIS Program, Aaron Anderson, PhD candidate in Mechanical and Science Engineering at Illinois Grainger Engineering, Matthew R. Berry, assistant professor in the Department of Veterinary Clinical Medicine at University of Illinois and Rebecca Bishop, an equine surgeon and emergency and critical care fellow at Illinois were awarded funds to develop advanced, non-invasive imaging tools to better detect and understand brain tumors (gliomas) in both humans and dogs. Using specialized magnetic resonance spectroscopy (MRS) and magnetic resonance elastography (MRE), the team aims to see how tumors function, looking beyond the limitations of a traditional MRI scan. Studying dogs with suspected gliomas will also help researchers test and predict how treatments might work in people, leading to improved diagnosis and therapy for both species. 


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This story was published September 30, 2025.