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

• Published in: IEEE transactions on medical imaging Vol. 24; no. 5; pp. 689 - 691
• Main Authors: Brown, R.A., Hongmei Zhu, Mitchell, J.R.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.05.2005; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial Intelligence; Biomedical image processing; Biomedical imaging; Concurrent computing; Diagnostic Imaging - methods; discrete Fourier transforms; distributed computing; Filtering; Fourier Analysis; Fourier transforms; Frequency; Image analysis; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image texture analysis; Imaging, Three-Dimensional - methods; Medical services; Numerical Analysis, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; vector processing; Wavelet transforms
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/TMI.2005.845320

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.