Distributed vector Processing of a new local MultiScale Fourier transform for medical imaging applications

Author

Brown, Robert A. ; Zhu, Hongmei ; Mitchell, J. Ross

Author_Institution

Seaman Family MR Res. Centre, Calgary, Canada

Volume

24

Issue

5

fYear

2005

fDate

5/1/2005 12:00:00 AM

Firstpage

689

Lastpage

691

Abstract

The recently developed S-transform (ST) combines features of the Fourier and Wavelet transforms; it reveals frequency variation over both space and time. It is a potentially powerful tool that can be applied to medical image processing including texture analysis and noise filtering. However, calculation of the ST is computationally intensive, making conventional implementations too slow for many medical applications. This problem was addressed by combining parallel and vector computations to provide a 25-fold reduction in computation time. This approach could help accelerate many medical image processing algorithms.

Keywords

Fourier transforms; biomedical MRI; image denoising; image texture; medical image processing; wavelet transforms; S-transform; distributed vector processing; local multiScale Fourier transform; medical image processing; noise filtering; texture analysis; wavelet transforms; Biomedical image processing; Biomedical imaging; Concurrent computing; Filtering; Fourier transforms; Frequency; Image analysis; Image texture analysis; Medical services; Wavelet transforms; Biomedical image processing; discrete Fourier transforms; distributed computing; vector processing; Algorithms; Artificial Intelligence; Diagnostic Imaging; Fourier Analysis; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Numerical Analysis, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;

fLanguage

English

Journal_Title

Medical Imaging, IEEE Transactions on

Publisher

ieee

ISSN

0278-0062

Type

jour

DOI

10.1109/TMI.2005.845320

Filename

1425674