Date/Time
Date(s) - 01/11/2010
5:00 pm - 6:00 pm
Abstract:
Diffusion weighted MRI is used to detect and stage neurodegenerative, malignant, and ischemic diseases. Correlation between pathology and the apparent diffusion coefficient relies on the design of phase encoding pulse sequences. The most common pulse approach encodes the diffusion coefficient as an exponential function. Recently, a novel “stretched” exponential model for diffusion induced signal decay has been suggested and applied. In this seminar, I will show how this new functional behavior can be derived directly from the Bloch-Torrey equation via fractional calculus.
Biographical Sketch:
Professor Magin completed undergraduate and graduate studies in physics at Georgia Tech (BS 69, MS 72) followed by additional graduate work in biophysics at the University of Rochester (PhD 76). He worked as a postdoctoral researcher for three years in the Laboratory of Chemical Pharmacology at the National Cancer Institute, NIH in the Laboratory of Chemical Pharmacology. In 1979 he joined the faculty in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He worked in Urbana for 18 years as an Assistant, Associate, and full Professor before joining the Department of Bioengineering at the University of Illinois at Chicago in 1998. He served as the BioE department head at UIC for 10 years and is currently a Professor in the Department of Bioengineering at UIC and directs the Diagnostic NMR Systems Laboratory. Professor Magin is a Fellow of the IEEE and AIMBE, and Editor of the Critical Reviews in Biomedical Engineering. In 1989-90 Dr. Magin spent a sabbatical year in the Department of Radiology of Shands Medical Center at the University of Florida in Gainesville, Florida. In 2006 Professor Magin received a Fulbright grant to lecture and conduct research in biomedical engineering at the Technical University of Kosice in Sovakia. Dr. Magin’s principal research interests involve magnetic resonance imaging, bioinstrumentation, and the modeling of biological systems.