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

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

doi:10.1109/TMI.2005.845320

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

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

Research

Research output: Contribution to journal › Article › peer-review

28 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 language	English (US)
Pages (from-to)	689-691
Number of pages	3
Journal	IEEE transactions on medical imaging
Volume	24
Issue number	5
DOIs	https://doi.org/10.1109/TMI.2005.845320
State	Published - 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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10.1109/TMI.2005.845320

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title = "Distributed vector processing of a new local multiscale Fourier transform for medical imaging applications",

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 = "Biomedical image processing, Discrete fourier transforms, Distributed computing, Vector processing",

author = "Brown, {Robert A.} and Hongmei Zhu and Mitchell, {J. Ross}",

note = "Funding Information: Manuscript received September 1, 2004; revised January 21, 2005. This work was supported in part by the Alberta Heritage Foundation for Medical Research (AHFMR), in part by the Multiple Sclerosis Society of Canada, and in part by the Natural Sciences and Engineering Research Council of Canada (NSERC). The Associate Editor responsible for coordinating the review of this paper and recommending its publication was P. Th{\'e}venaz. Asterisk indicates corresponding author. *R. A. Brown is with the Department of Electrical and Computer Engineering, University of Calgary and the Seaman Family MR Research Centre, Foothills Medical Centre, 1403 29 St. N.W., Calgary, AB T2N 2T9, Canada (e-mail: brownr@ucalgary.ca).",

year = "2005",

month = may,

doi = "10.1109/TMI.2005.845320",

language = "English (US)",

volume = "24",

pages = "689--691",

journal = "IEEE Transactions on Medical Imaging",

issn = "0278-0062",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "5",

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T1 - Distributed vector processing of a new local multiscale Fourier transform for medical imaging applications

AU - Brown, Robert A.

AU - Zhu, Hongmei

AU - Mitchell, J. Ross

N1 - Funding Information: Manuscript received September 1, 2004; revised January 21, 2005. This work was supported in part by the Alberta Heritage Foundation for Medical Research (AHFMR), in part by the Multiple Sclerosis Society of Canada, and in part by the Natural Sciences and Engineering Research Council of Canada (NSERC). The Associate Editor responsible for coordinating the review of this paper and recommending its publication was P. Thévenaz. Asterisk indicates corresponding author. *R. A. Brown is with the Department of Electrical and Computer Engineering, University of Calgary and the Seaman Family MR Research Centre, Foothills Medical Centre, 1403 29 St. N.W., Calgary, AB T2N 2T9, Canada (e-mail: brownr@ucalgary.ca).

PY - 2005/5

Y1 - 2005/5

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AB - 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.

KW - Biomedical image processing

KW - Discrete fourier transforms

KW - Distributed computing

KW - Vector processing

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

Abstract

Keywords

ASJC Scopus subject areas

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