Plenary Event
Signal, Image, and Data Processing Keynote
20 August 2024 • 2:30 PM - 3:15 PM PDT | Conv. Ctr. Room 17B
Session Chair: Khan Iftekharuddin, Old Dominion Univ. (United States)
2:30 PM - 2:35 PM:
Welcome and Opening Remarks
2:35 PM - 3:15 PM:
AI-powered MRI: towards an omni imaging technology for brain mapping
The ongoing paradigm shift in healthcare towards personalized and precision medicine is posing a critical need for noninvasive imaging technology that can provide quantitative tissue and molecular information. Magnetic resonance signals from biological systems contain information from multiple molecules and multiple physical/biological processes (e.g., T1 relaxation, T2 relation, diffusion, perfusion, etc.). So, magnetic resonance imaging (MRI) is inherently a high-dimensional imaging technology that can acquire structural, functional and molecular information simultaneously. In practice, due to the curse of dimensionality, MRI experiments are often done in a low-dimensional setting to acquire biomarkers one at a time. Such a “divide-and-conquer” approach not only reduces data acquisition efficiency but also makes it difficult to obtain molecular information in high resolution. By synergistically integrating machine learning with sparse sampling, constrained image reconstruction and quantum simulation, we have successfully demonstrated ultrafast high-dimensional imaging of the brain. This talk will give an overview of this unprecedented omni imaging technology and show some exciting experimental results of brain function and diseases.
Zhi-Pei Liang is currently the Franklin W. Woeltge Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC). His research is in the general area of magnetic resonance imaging, signal processing and machine learning. His work has been recognized by a number of awards, including the Sylvia Sorkin Greenfield Award (Medical Physics, 1990), Whitaker Biomedical Engineering Research Award (1991), NSF CAREER Award (1995), University Scholar Award (UIUC, 2001), Isidor I. Rabi Award (ISMRM, 2009), Otto Schmitt Award (IFMBE, 2012), IEEE-EMBC Best Paper Awards (2010, 2011, 2021), IEEE-ISBI Best Paper Award (2010, 2015), Technical Achievement Award (IEEE-EMBS, 2014), Gold Medal (ISMRM, 2022). Dr. Liang is a Fellow of NAI, IEEE, ISMRM, AIMBE and IAMBE. He served as President of the IEEE-EMBS from 2011-2012 and Chair-elect of the Int’l Academy of Medical and Biological Engineering from 2022-2024.
MENU: Coffee, decaf, and tea will be available outside the presentation room.
SETUP: Theater style seating. .
2:30 PM - 2:35 PM:
Welcome and Opening Remarks
2:35 PM - 3:15 PM:
AI-powered MRI: towards an omni imaging technology for brain mapping
 |
Zhi-Pei Liang
Univ. of Illinois at Urbana-Champaign (United States) |
The ongoing paradigm shift in healthcare towards personalized and precision medicine is posing a critical need for noninvasive imaging technology that can provide quantitative tissue and molecular information. Magnetic resonance signals from biological systems contain information from multiple molecules and multiple physical/biological processes (e.g., T1 relaxation, T2 relation, diffusion, perfusion, etc.). So, magnetic resonance imaging (MRI) is inherently a high-dimensional imaging technology that can acquire structural, functional and molecular information simultaneously. In practice, due to the curse of dimensionality, MRI experiments are often done in a low-dimensional setting to acquire biomarkers one at a time. Such a “divide-and-conquer” approach not only reduces data acquisition efficiency but also makes it difficult to obtain molecular information in high resolution. By synergistically integrating machine learning with sparse sampling, constrained image reconstruction and quantum simulation, we have successfully demonstrated ultrafast high-dimensional imaging of the brain. This talk will give an overview of this unprecedented omni imaging technology and show some exciting experimental results of brain function and diseases.
Zhi-Pei Liang is currently the Franklin W. Woeltge Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC). His research is in the general area of magnetic resonance imaging, signal processing and machine learning. His work has been recognized by a number of awards, including the Sylvia Sorkin Greenfield Award (Medical Physics, 1990), Whitaker Biomedical Engineering Research Award (1991), NSF CAREER Award (1995), University Scholar Award (UIUC, 2001), Isidor I. Rabi Award (ISMRM, 2009), Otto Schmitt Award (IFMBE, 2012), IEEE-EMBC Best Paper Awards (2010, 2011, 2021), IEEE-ISBI Best Paper Award (2010, 2015), Technical Achievement Award (IEEE-EMBS, 2014), Gold Medal (ISMRM, 2022). Dr. Liang is a Fellow of NAI, IEEE, ISMRM, AIMBE and IAMBE. He served as President of the IEEE-EMBS from 2011-2012 and Chair-elect of the Int’l Academy of Medical and Biological Engineering from 2022-2024.
Event Details
FORMAT: General session with live audience Q&A to follow presentations.MENU: Coffee, decaf, and tea will be available outside the presentation room.
SETUP: Theater style seating. .