Noise suppression in cone beam CT projection data
View Patent ↗A method for suppressing noise in a diagnostic 3-D image, executed at least in part on a logic processor, captures, at each of a number of projection angles, 2-D image projection data, wherein each 2-D image projection has a central pixel and arranges the 2-D image projection data to form a 3-D data set. Each of the 2-D image projections is processed by performing a diffusion filtering process that obtains a homogeneity value for the 3-D data set, generates a diffusion conductance function according to an intensity gradient between adjacent digital image elements, and applies the diffusion filtering process to digital image elements according to the obtained homogeneity value, the generated diffusion conductance function, and a weighting value that relates to the distance of each pixel in the projection from the central pixel. The diagnostic 3-D image is reconstructed from the processed 2-D image projections.
1. A method for filtering a plurality of 2-D x-ray projection images of a subject for use in a 3-D image reconstruction, the method comprising:
processing each of the plurality of 2-D x-ray project images by, for each pixel of a plurality of pixels in each 2-D projection image:
computing a variable weight value according to the distance between each pixel and a central pixel of the 2-D projection image upon which a central x-ray has been incident; and
applying a diffusion process for each pixel with a fixed weight value for in-plane adjacent pixels and the variable weight value for out-of-plane adjacent pixels;
reconstructing a diagnostic 3-D image from the plurality of processed 2-D x-ray projection images; and
transmitting, storing, or displaying the reconstructed diagnostic 3-D image.
2. The method of claim 1 wherein the step of applying the diffusion process repeats one or more times.
3. The method of claim 1 wherein applying the diffusion process further comprises:
obtaining a homogeneity value for the plurality of 2-D x-ray projection images; and
generating a diffusion conductance function according to an intensity gradient between adjacent digital image elements.
4. The method of claim 1 wherein applying a diffusive filtering process comprises:
obtaining a homogeneity value for the 3-D data set;
generating a diffusion conductance function according to an intensity gradient between adjacent digital image elements from the projection data; and
applying the diffusion filtering process to a plurality of digital image elements according to the obtained homogeneity value, the generated diffusion conductance function, and one of the weight values.
5. The method of claim 4 wherein the generated diffusion conductance function reduces the magnitude of intensity differences or gradient for one or more pairs of digital image elements.
6. The method of claim 4 wherein obtaining the homogeneity value further comprises receiving an operator entry.
7. The method of claim 4 wherein obtaining a homogeneity value for the 3-D data set comprises computing an average value of magnitude of intensity differences or gradient for two or more digital image elements.
8. The method of claim 7 further comprising computing a standard deviation for the magnitude of intensity differences or gradient for pairs of pixels.