2013 IEEE International Ultrasonics Symposium (IUS) 2013
DOI: 10.1109/ultsym.2013.0315
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Improvement of axial spatial resolution of ultrasound image using Wiener filter for measurement of intima-media thickness of carotid artery

Abstract: Measurement of intima-media thickness (IMT) of the carotid artery by ultrasonography is widely used for diagnosis of atherosclerosis. For accurate measurement of IMT, in the present study, a method based on the Wiener filter was developed for improvement of image spatial resolution. There are many studies on improvement of spatial resolution for elimination of the point spread function (PSF) of a system using a deconvolution filter. PSF is determined by the transfer function H(f ) (including transfer function … Show more

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Cited by 4 publications
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“…Various other techniques combine impulse removal filters with local adaptive filtering in the transform domain to remove not only white and mixed noise, but also their mixtures (Rabbani, Vafadust, Abolmaesumi, & Gazor, 2008). In order to reduce the presence of noise in medical images many techniques are available from the past such as linear filtering (Simon,VanBaren & Ebbini, 1998) adaptive filtering (Weiner Filters) (Hasegawa, Kageyama & Kanai, 2013) and median filtering (Czerwinski, Jones & O'Brien, 1995). However, digital filters, linear filters and adaptive filters proved to reduce noise in stationary signals.…”
Section: Introductionmentioning
confidence: 99%
“…Various other techniques combine impulse removal filters with local adaptive filtering in the transform domain to remove not only white and mixed noise, but also their mixtures (Rabbani, Vafadust, Abolmaesumi, & Gazor, 2008). In order to reduce the presence of noise in medical images many techniques are available from the past such as linear filtering (Simon,VanBaren & Ebbini, 1998) adaptive filtering (Weiner Filters) (Hasegawa, Kageyama & Kanai, 2013) and median filtering (Czerwinski, Jones & O'Brien, 1995). However, digital filters, linear filters and adaptive filters proved to reduce noise in stationary signals.…”
Section: Introductionmentioning
confidence: 99%