Dr. Mark Chiew, Department of Medical Biophysics, University of Toronto, will lecture on, "Self-supervised learning and friends – computational methods for MRI in incomplete and corrupted data regimes."
Abstract: In this talk, I will discuss some recent research work in my group, which is focused on image acquisition and reconstruction methods for rapid and robust MRI. I will introduce our recent work on self-supervised learning for accelerated image reconstruction, and extensions of that work in joint denoising and reconstruction tasks and multi-contrast imaging. I will also highlight some recent work focusing on robust multi-shot EPI at 7T, in which structured low-rank methods are used to improve image quality and stability that arise due to inter-shot phase fluctuations and motion. Finally, I will provide a brief survey other recent research, which includes developing robust reconstruction for imaging awake, behaving non-human primates, ultra-high resolution fMRI at 7T using a radial-cartesian acquisition, accelerated parallel transmit mapping, and uncertainty quantification in low-rank denoising of MRSI data.
Bio: Mark Chiew is a Tier 2 Canada Research Chair, Associate Professor at the University of Toronto, and a Scientist at Sunnybrook Research Institute. Mark obtained his PhD from the University of Toronto, working on methods for real-time fMRI applied to stroke recovery. Following his PhD, he spent 10 years in Oxford, first as a post-doc under the supervision of Prof. Karla Miller working on low-rank accelerated fMRI at 7T, and then subsequently as an early career faculty member with a UK Royal Academy of Engineering fellowship. In 2022, he moved back to Toronto to start a new research group focusing on the development of computational imaging methods for MRI, with an in emphasis towards clinical imaging applications. His research interests include data acquisition and image reconstruction methods for MRI, computational imaging and recently self-supervised learning methods, with applications ranging from fMRI, ASL, MRSI, and structural imaging.
