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After reconstruction with filtered backprojection using a Gaussian filter of 7 mm the measured resolution was 8.71 and 9.74 mm, respectively.
The images were smoothed using a Gaussian filter (2 mm).
Smoothing: the image is smoothed using a Gaussian filter to remove noise.
Images were smoothed using a Gaussian filter (8.4 mm at full width half maximum).
Tomographic images were reconstructed (OSEM 6i/16s) using a Gaussian filter (full width half maximum (FWHM): Γ0 = 4 mm).
Finally, the normalized gray matter images were smoothed using a Gaussian filter (8 mm full-width half-maximum, FWHM).
Post-reconstruction smoothing filtering was applied using a Gaussian filter with 1.5- or 2.5-mm kernel size.
Finally, spatial smoothing was performed on the functional images using a Gaussian filter (8 mm full width half-maximum, FWHM).
The final images presented in the figures were further smoothened in the frequency domain using a Gaussian filter.
In the Canny algorithm, an image is smoothed using a Gaussian filter with a specified standard deviation,, to reduce noise.
Segmentation is divided into the following steps: Smoothing: the image is smoothed using a Gaussian filter to remove noise.
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