Novel Application of Nonlinear Apodization for Medical Imaging

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Novel Application of Nonlinear Apodization for Medical Imaging


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Novel Application of Nonlinear Apodization for Medical Imaging

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Presented here is a nonlinear apodization (NLA) method for processing magnetic resonance (MR) and ultrasound (US) images, which has been modified from its original use in processing radar imagery. This technique reduces Gibb?s artifacts (ringing) while preserving the boundary edges and the mainlobe width of the impulse response. This is done by selecting, pixel-by-pixel, the specific signal-domain windowing function (cosine-on-pedestal) that optimizes each point throughout the image. The windows are chosen from an infinite but bounded set, determined by weighting coefficients for the cosine-on-pedestal equation and the values of the pixels adjacent to the point of interest. By using this method, total sidelobe suppression is achievable without degrading the resolution of the mainlobe. In radar applications, this nonlinear apodization technique has shown to require fewer operations per pixel than other traditional apodization techniques. The preliminary results from applications on MR and US data are presented here.
Presented here is a nonlinear apodization (NLA) method for processing magnetic resonance (MR) and ultrasound (US) images, which has been modified from its original use in processing radar imagery. This technique reduces Gibb?s artifacts (ringing) while preserving the boundary edges and the mainlobe width of the impulse response. This is done by selecting, pixel-by-pixel, the specific signal-domain windowing function (cosine-on-pedestal) that optimizes each point throughout the image. The windows are chosen from an infinite but bounded set, determined by weighting coefficients for the cosine-on-pedestal equation and the values of the pixels adjacent to the point of interest. By using this method, total sidelobe suppression is achievable without degrading the resolution of the mainlobe. In radar applications, this nonlinear apodization technique has shown to require fewer operations per pixel than other traditional apodization techniques. The preliminary results from applications on MR and US data are presented here.