About

Pengfei Song, PhD, is an Assistant Professor and Y. T. Lo Faculty Fellow at the Department of Electrical and Computer Engineering at the University of Illinois Urbana-Champaign. He is also an affiliate faculty member with the Beckman Institute for Advanced Science and Technology, Department of Bioengineering, Neuroscience Program, Cancer Center at Illinois, Carl R. Woese Institute for Genomic Biology, and Carle Illinois College of Medicine. Dr. Song obtained his PhD in Biomedical Engineering from Mayo Clinic College of Medicine and Science in 2014 and completed postdoctoral training at Mayo Clinic under the supervision of Profs. James Greenleaf and Shigao Chen until 2018. His research interests include ultrafast ultrasound imaging, super-resolution ultrasound, functional ultrasound, 3D ultrasound imaging, deep learning, and ultrasound shear wave elastography. He has published extensively in peer-reviewed journals, holds several patents licensed and used worldwide in clinical settings, and has delivered numerous invited presentations. Dr. Song has received multiple awards, including the NIH K99/R00 Pathway to Independence Award, NSF CAREER Award, and the NIBIB Trailblazer Award. His research program is continuously funded by NIH, DOD, and NSF, and he is recognized as a Fellow of the American Institute of Ultrasound in Medicine, a Senior Member of the National Academy of Inventors and IEEE, and a Full Member of the Acoustical Society of America.

Research topics

• Computer Science
• Artificial Intelligence
• Radiology
• Pathology
• Physics
• Nuclear medicine
• Medicine
• Chemistry
• Optics
• Biomedical engineering

Selected publications

• Short Acquisition Time Super-Resolution Ultrasound Microvessel Imaging via Microbubble Separation

  Scientific Reports · 2020 · 166 citations

  • Computer Science
  • Artificial Intelligence
  • Computer Science

  Super-resolution ultrasound localization microscopy (ULM), based on localization and tracking of individual microbubbles (MBs), offers unprecedented microvascular imaging resolution at clinically relevant penetration depths. However, ULM is currently limited by the requirement of dilute MB concentrations to ensure spatially sparse MB events for accurate localization and tracking. The corresponding long imaging acquisition times (tens of seconds or several minutes) to accumulate sufficient isolated MB events for full reconstruction of microvasculature preclude the clinical translation of the technique. To break this fundamental tradeoff between acquisition time and MB concentration, in this paper we propose to separate spatially overlapping MB events into sub-populations, each with sparser MB concentration, based on spatiotemporal differences in the flow dynamics (flow speeds and directions). MB localization and tracking are performed for each sub-population separately, permitting more robust ULM imaging of high-concentration MB injections. The superiority of the proposed MB separation technique over conventional ULM processing is demonstrated in flow channel phantom data, and in the chorioallantoic membrane of chicken embryos with optical imaging as an in vivo reference standard. Substantial improvement of ULM is further demonstrated on a chicken embryo tumor xenograft model and a chicken brain, showing both morphological and functional microvasculature details at super-resolution within a short acquisition time (several seconds). The proposed technique allows more robust MB localization and tracking at relatively high MB concentrations, alleviating the need for dilute MB injections, and thereby shortening the acquisition time of ULM imaging and showing great potential for clinical translation.

  DOI

Recent grants

• Early prediction of colorectal liver metastases treatment response with ultrasound microvessel imaging

  NIH · $684k · 2017–2023

• A novel transducer clip-on device to enable accessible and functional 3D ultrasound imaging

  NIH · $2.1M · 2022–2027

• NIH Grant K99CA214523

  NIH · $334k · 2019

• Development of Super-resolution Ultrasound Localization Microscopy for Imaging Vascular Biomarkers of Alzheimer Disease

  NIH · $927k · 2020–2024

• CAREER: Super-resolution Ultrasound Imaging for High-resolution Functional Mapping of the Brain

  NSF · $500k · 2023–2025

Frequent coauthors

• Shigao Chen

  Mayo Clinic in Arizona

  164 shared

• Matthew R. Lowerison

  74 shared

• James F. Greenleaf

  Mayo Clinic in Florida

  59 shared

• Matthew W. Urban

  WinnMed

  54 shared

• Chengwu Huang

  Mayo Clinic

  50 shared

• Zhijie Dong

  University of Illinois Urbana-Champaign

  47 shared

• Richard Pazdur

  46 shared

• Shenghui Tang

  45 shared

Labs

• Bioengineering at IllinoisPI

Education

• PhD, Biomedical Engineering

  Mayo Clinic College of Medicine and Science

  2014

Awards & honors

• NIH K99/R00 Pathway to Independence Award
• NSF CAREER Award
• NIBIB Trailblazer Award
• IEEE Ultrasonics Early Career Investigator Award
• Chan Zuckerberg Initiative (CZ) Early Career Acceleration Aw…

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