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Distributed Vector Processing of A New Local Multiscale: Fourier Transform for Medical Imaging Applications

dc.contributor.authorBrown, Robert
dc.contributor.authorZhu, Hongmei
dc.contributor.authorMitchell, Joseph
dc.date.accessioned2007-03-29T23:24:03Z
dc.date.available2007-03-29T23:24:03Z
dc.date.issued2005
dc.description.abstractThe recently developed S-transform (ST) combines features of the Fourier andWavelet 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.
dc.identifier.citationR. A. Brown, Hongmei Zhu and J. R. Mitchell, "Distributed Vector Processing of a New Local MultiScale Fourier Transform for Medical Imaging Applications," in IEEE Transactions on Medical Imaging, vol. 24, no. 5, pp. 689-691, May 2005. doi: 10.1109/TMI.2005.845320
dc.identifier.issn0278-0062
dc.identifier.urihttp://hdl.handle.net/10315/927
dc.identifier.urihttps://doi.org/10.1109/TMI.2005.845320
dc.language.isoen
dc.publisherIEEE Transactions on Medical Imaging
dc.subjectBiomedical image processing
dc.subjectdiscrete Fourier transforms
dc.subjectdistributed computing
dc.subjectvector processing
dc.titleDistributed Vector Processing of A New Local Multiscale: Fourier Transform for Medical Imaging Applications
dc.typeArticle

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