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Radiology Paging a Good Mathematician: Why Math Can Contribute More to Medicine Than You Might Think

Award: Trevor Evans

Year of Award: 2009

Publication Information: Math Horizons, April 2008, pp. 5-9

Summary: In this presentation of applied mathematics in practice, Richard A. Guyer explains how mathematics is used in various ways with MRI and provides descriptive images to help his audience better understand this diagnostic tool. This includes an explanation of the use of Fourier transforms and signal processing to convert a signal to an image, and how quantitative information about an organ can be derived from such images.

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About the Author: (From the Prizes and Awards Booklet, MathFest 2009)  Richard Guyer is a 2006 graduate of Davidson College, where he studied mathematics and economics. After spending much of his time in college considering a career in academic economics or mathematics, he became interested in medicine. His time in the Mathematics Department at Davidson planted seeds of interest in applications of mathematics to medicine. Following graduation, he attended the post-baccalaureate Premedical Program at the University of Pennsylvania, where he was fortunate enough to work under outstanding researchers in the Department of Radiology. This work further sharpened his interest in the relationship between mathematics and medicine. Currently, he is a medical student at the University of Virginia planning for a career in academic medicine. Although he has not yet decided what field of medicine to specialize in, he is looking forward to applying his mathematical background in whatever specialty he ultimately chooses.

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Richard A. Guyer
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Richard A. Guyer
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Publication Date: 
Sunday, August 23, 2009
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Summary: 

In this presentation of applied mathematics in practice, Richard A. Guyer explains how mathematics is used in various ways with MRI and provides descriptive images to help his audience better understand this diagnostic tool. This includes an explanation of the use of Fourier transforms and signal processing to convert a signal to an image, and how quantitative information about an organ can be derived from such images.

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