Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences


UC Berkeley


Joint Colloquium Distinguished Lecture Series

Sampling Theory and Adaptive Acquisition for Cardiac Magnetic Resonance Imaging

photo of Yoram Bresler Wednesday, February 14, 2007
306 Soda Hall (HP Auditorium)
4:00 - 5:00 pm

Yoram Bresler
Coordinated Science Laboratory and Departments of Electrical and Computer Engineering and BioEngineering, University of Illinois at Urbana-Champaign

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Heart disease is the leading cause of death in the western world. Early diagnosis, therapy management, and surgical intervention all require improved methods for cardiac imaging. Cardiac Magnetic Resonance Imaging (CMRI) holds the promise of replacing the gold standard of invasive catheterization and x-ray imaging by benign radio frequency waves and magnetic fields. However, MR imaging of the beating heart is a significant technological challenge. While CMRI is already a clinical tool in hospitals, it does not offer sufficient temporal resolution, its spatial resolution is insufficient to discern small blocked arteries, and it requires long breath-holds that can not be performed by infants or the sick.

We describe a model-based patient-adaptive approach for real-time cardiac imaging that that addresses these difficulties. Unlike previous methods, the current approach produces a movie ("cine") in which each reconstructed heartbeat is temporally resolved, rather than being a composite or weighted average of multiple actual heartbeats. The model used in the method captures the spatial and temporal-spectral characteristics of the heart. The model parameters are estimated as part of the MRI experiment and drive both data acquisition and cine reconstruction algorithm. The approach relies on a formulation of dynamic MRI as a time-sequential sampling (TSS) problem, where only one sample of the spatial Fourier transform of the object can be acquired at any one time. The TSS theory provides a design for minimum redundancy data acquisition and reconstruction optimized for the dynamic object being imaged. An extension of the method enables ungated free-breathing real-time cardiac imaging, by accounting in the model for both cardiac and respiratory motion during imaging. Another extension of the theory to multi-channel time-sequential sampling, takes advantage of parallel multi-channel receiver coil array hardware commonly available in modern MR scanners, to provide further improvements in temporal and spatial resolutions and signal-to-noise ratio. The methods are demonstrated by simulation and in-vivo experiments producing high temporal and spatial resolution movies of the heart, with multifold reduction in acquisition rate requirements compared to conventional methods.

Work with: Nitin Aggarwal, Behzad Sharif, Qi Zhao, and Saptarshi Bandyopadhyay


Yoram Bresler received the B.Sc. (cum laude) and M.Sc. degrees from the Technion, Israel Institute of Technology, in 1974 and 1981 respectively, and the Ph.D degree from Stanford University, in 1986, all in Electrical Engineering. In 1987 he joined the University of Illinois at Urbana-Champaign, where he is currently a Professor at the Departments of Electrical Computer Engineering and Bioengineering, and Research Professor at the Coordinated Science Laboratory. His current research interests include multi-dimensional and statistical signal processing and their applications to inverse problems in imaging.

Dr. Bresler was an Associate Editor for the IEEE Transactions on Image Processing in 1992-93, on the editorial board of Machine Vision and Applications in 1991-2004 and a member of the IEEE Image and Multidimensional Signal Processing Technical Committee in 1994-1998. Currently he is on the editorial board of the SIAM Journal on Imaging Science, on the editorial board of the IEEE Journal on Selected Topics in Signal Processing, and on the IEEE Biomaging and Signal Processing Technical Committee. In 1988 and 1989 he received the Senior Paper Awards from the IEEE Signal Processing society, and a paper he coauthored with his student received the Young Author Award from the same society in 2002. He is the recipient of a 1991 NSF Presidential Young Investigator Award, the Technion (Israel Inst. of Technology) Fellowship in 1995, and the Xerox Senior Award for Faculty Research in 1998. He was named a University of Illinois Scholar in 1999, and appointed as an Associate at the Center for Advanced Study of the University in 2001-2. In 2005-6 he was a Faculty Fellow at the National Center for Supercomputing Applications in Urbana, IL.

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