Brad Sutton

Brad Sutton
Brad Sutton
  • Professor
(217) 244-5154
1215C Beckman Institute

Primary Research Area

  • Bioimaging at Multi-Scale

Research Areas

  • Biomedical imaging
  • Diffusion weighted imaging
  • Dynamic imaging
  • Functional MRI
  • Image reconstruction
  • Instrumentation
  • Magnetic susceptibility
  • MRI
  • Neural engineering (general)
  • Neuromuscular coupling
  • Systems modeling approaches to understand brain function

For More Information

Biography

Dr. Sutton joined the Bioengineering Department at the University of Illinois in January, 2006. Dr. Sutton received a B.S. in General Engineering from the University of Illinois at Urbana-Champaign. He earned M.S.'s in Biomedical and Electrical Engineering and a PhD in Biomedical Engineering from the University of Michigan in 2003. He has affiliations with the Beckman Institute, Electrical and Computer Engineering Department, and the Neuroscience Program. His research interests are in developing magnetic resonance imaging acquisition, image reconstruction, and systems modeling approaches to understand brain function.

Education

  • Ph.D., Biomedical Engineering, University of Michigan, 2003

Service to Federal and State Government

  • NIH ad hoc review panels, 2018-2021.

Research Interests

  • Neuromuscular coupling
  • Image Reconstruction
  • Magnetic Susceptibility
  • Diffusion Weighted Imaging
  • Dynamic Imaging
  • Functional Magnetic Resonance Imaging

Research Statement

My research is focused on developing novel methods to image structure and physiological function with magnetic resonance imaging. Application areas include functional neuroimaging and dynamic imaging of muscle function in speech.

Undergraduate Research Opportunities

During various disease states and even during healthy aging, the human brain undergoes dramatic changes in structural and functional organization, along with changes in metabolic support structures. Magnetic resonance imaging offers many windows into this changing physiology. Analysis of such changes requires applications of linear algebra and statistics upon very large data sets. Currently, there are positions for undergraduates to learn and apply structural analysis methodologies to disease populations such as multiple sclerosis.

Primary Research Area

  • Bioimaging at Multi-Scale

Research Areas

  • Biomedical imaging
  • Diffusion weighted imaging
  • Dynamic imaging
  • Functional MRI
  • Image reconstruction
  • Instrumentation
  • Magnetic susceptibility
  • MRI
  • Neural engineering (general)
  • Neuromuscular coupling
  • Systems modeling approaches to understand brain function

Selected Articles in Journals

Articles in Conference Proceedings