Pengfei Song, an assistant professor of electrical and computer engineering, will present "In vivo micron-scale deep tissue microvascular imaging with super-resolution ultrasound" at the Beckman Institute Director's Seminar at noon on Thursday, Nov. 3 in 1005 Beckman and on Zoom. Lunch will be provided to in-person attendees.
In vivo micron-scale deep tissue microvascular imaging with super-resolution ultrasound
Super-resolution ultrasound imaging is an emerging technology that uses contrast microbubbles to achieve micron-scale imaging resolution and deep imaging penetration. The unprecedented combination of high spatial resolution and depth of penetration opened new doors for many enticing biomedical applications based on microvascular biomarkers. In this talk, I will first introduce the principles of conventional super-resolution ultrasound imaging, and then present several novel techniques developed by our group that enhance the in vivo imaging performance of super-resolution ultrasound. I will introduce several fast super-resolution imaging methods based on spatiotemporal filtering, sparsity-promoting algorithms, and deep learning. I will then introduce a new 3D super-resolution imaging method based on 2D row-column-addressing arrays and deep learning-based beamforming. Accompanying the technical themes, I will also present examples of preclinical and clinical applications of super-resolution ultrasound imaging in the domains of cancer and Alzheimer’s disease.
Pengfei Song is an assistant professor in the Department of Electrical and Computer Engineering, the Department of Bioengineering, and the Carle
Illinois College of Medicine. He is a full-time faculty member at the Beckman Institute for Advanced Science and Technology in the Photoacoustic Imaging Group. Before joining Illinois, he obtained his Ph.D. degree and conducted his postdoctoral
training under the supervision of Drs. James Greenleaf and Shigao Chen at Mayo Clinic. His research interests include ultrafast ultrasound imaging, super-resolution ultrasound, deep learning, and ultrasound elastography. Dr. Song has published
over 80 peer-reviewed journal papers. He holds several patents that have been licensed and commercialized by major ultrasound companies and used worldwide in the clinic. Dr. Song has delivered over a dozen invited presentations at prominent international
conferences including the Gordon Research Conference. Dr. Song is an awardee of the NIH K99/R00 Pathway to Independence Award and the NIH/NIBIB Trailblazer Award. He recently received the Dean’s Award for Excellence in Research for Assistant
Professor from the Grainger College of Engineering. He is an elected Fellow of the American Institute of Ultrasound in Medicine, a Senior Member of the National Academy of Inventors, a Senior Member of IEEE, and a Full Member of the Acoustical
Society of America.