Distributed vector processing of a new local multiscale Fourier transform for medical imaging applications

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

Research output: Contribution to journalArticle

25 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)689-691
Number of pages3
JournalIEEE transactions on medical imaging
Volume24
Issue number5
DOIs
StatePublished - May 2005

Keywords

  • Biomedical image processing
  • Discrete fourier transforms
  • Distributed computing
  • Vector processing

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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