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Wavelets Are Enhancing Medical Imaging

M. Unser, A. Aldroubi, A. Laine

Exploring Science and Medical Discoveries: Medical Imaging, C.F. Naff, Ed., Thompson Gale (Greenhaven Press), Detroit MI, USA, pp. 175-179, 2005.



Experts generally agree that the biggest advance in medical imaging in the last two decades of the twentieth century was the use of computers to assemble data from imaging devices into highly detailed pictures. Computed tomography, magnetic resonance imaging, and positron emission tomography all rely on computers to make sense of the data collected by the machines. To dos so, computer programs increasingly depend on wavelets. These are mathematical tools, first developed in the early twentieth century, that allow wave data at various scales to be integrated into a whole. They have proven extremely useful in computerized medical imaging.

In the selection that follows three experts describe the boom in wavelet applications. In particular, they mention the usefulness of wavelets in screening out “noise”—the technical term for random perturbations on a signal. Wavelets also prove useful in tomography, the assembly of shots from multiple angles into a sectional image. Wavelets hold promise for helping radiologists detect signs of cancer in computer-aided mammography as well. The authors conclude that wavelets are integral to understanding wave data, such as that generated by imaging devices. Michael Unser is a professor of biomedical imaging at the Swiss Federal Institute of Technology, Lausanne. Akram Aldroubi is a professor of mathematics at Vanderbilt University. Andrew Laine is a professor of biomedical engineering at Columbia University.


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