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Medical Physics / Volume 30 / Issue 6 / RADIATION THERAPY PHYSICS

Med. Phys. 30, 1134 (2003); http://dx.doi.org/10.1118/1.1576931 (8 pages)

A new local multiscale Fourier analysis for medical imaging

H. Zhu, B. G. Goodyear, M. L. Lauzon, A. G. Law, and J. R. Mitchell

Departments of Radiology and Clinical Neurosciences, University of Calgary, Seaman Family MR Research Centre, Foothills Medical Centre, 1403-29th Street NW, Calgary, Alberta T2N 2T9, Canada

R. A. Brown, G. S. Mayer,

Department of Electrical and Computer Engineering, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada

L. Mansinha

Department of Earth Sciences, University of Western Ontario Biological and Geological Bldg., London, Ontario N6A 5B7, Canada

(Received 2 December 2002; accepted 1 April 2003; published online 29 May 2003)

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The Stockwell transform (ST), recently developed for geophysics, combines features of the Fourier, Gabor and wavelet transforms; it reveals frequency variation over time or space. This valuable information is obtained by Fourier analysis of a small segment of a signal at a time. Localization of the Fourier spectrum is achieved by filtering the signal with frequency-dependent Gaussian scaling windows. This multi-scale time–frequency analysis provides information about which frequencies occur and more importantly when they occur. Furthermore, the Stockwell domain can be directly inferred from the Fourier domain and vice versa. These features make the ST a potentially effective tool to visualize, analyze, and process medical imaging data. The ST has proven useful in noise reduction and tissue texture analysis. Herein, we focus on the theory and effectiveness of the ST for medical imaging. Its effectiveness and comparison with other linear time–frequency transforms, such as the Gabor and wavelet transforms, are discussed and demonstrated using functional magnetic resonance imaging data. © 2003 American Association of Physicists in Medicine.

© 2003 American Association of Physicists in Medicine

Digital Object Identifier
http://dx.doi.org/10.1118/1.1576931

KEYWORDS and PACS

Keywords

Fourier analysis, biomedical MRI, brain, Fourier transforms, wavelet transforms, medical image processing, pneumodynamics, biomechanics, Fourier transform, wavelet transform, Stockwell transform, motion artifacts

PACS

PUBLICATION DATA

ISSN

0094-2405 (print)  

Publisher

$abstract.society.value is a Member of CrossRef American Association of Physicists in Medicine

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