Seminar: Mathews Jacob, Iowa University
Join The Ohio State University Department of Electrical and Computer Engineering (ECE) for a special seminar by Dr. Mathews Jacob, Iowa University.
Modern MRI machines are highly versatile, enabling the in-vivo visualization of various biophysical parameters of the tissue. However, the slow nature of image acquisition, as well as calibration errors, introduce several inconvenient tradeoffs, including long scan time, low temporal resolution, and the presence of artifacts resulting from subject motion and scanner non-idealities. These tradeoff results in several challenges in multidimensional MRI. Learning-based algorithms to overcome the above problems will be introduced for a variety of applications, including cardio-vascular applications on subjects that have difficulty holding their breath. The central idea is to learn and exploit the significant structure in the data resulting from image content as well as multi-channel/multishot acquisition. Self-learning strategies, where the structure is learned from the measured data itself, as well as exemplary schemes that learn the structure from training data, will be introduced. This talk is a summary of the recent work from the group, which is available at:
Mathews Jacob is an associate professor at the Department of Electrical and Computer Engineering and is heading the Computational Biomedical Imaging Group (CBIG) at the University of Iowa. His research interests include image reconstruction, image analysis, and quantification in the context of magnetic resonance imaging. He obtained his B.Tech in Electronics and Communication Engineering from National Institute of Technology, Calicut, Kerala, and M.E in signal processing from the Indian Institute of Science, Bangalore. He received his Ph.D. degree from the Biomedical Imaging Group at the Swiss Federal Institute of Technology. He was a Beckman postdoctoral fellow at the University of Illinois at Urbana Champaign between 2003 and 2006. He is the recipient of the CAREER award from the National Science Foundation in 2009 and the Research Scholar Award from American Cancer Society in 2011. He is currently the associate editor of the IEEE Transactions on Medical Imaging and IEEE Transactions on Computational Imaging.