MRI Gibbs' ringing filtering with edge-protection

1. A magnetic resonance imaging (MRI) processor system comprising:

memory configured to contain data arrays representing an image of patient anatomy in a k-space domain and in a spatial image domain,

a data array in one of said domains being transformable into the other of said domains by Fourier Transformation; and

at least one data processor configured to

low-pass filter the data array, in at least one of

(a) the k-space domain or

(b) the spatial image domain of said image of patient anatomy,

to produce a low-pass filtered data array in the k-space domain or the spatial image domain;

wherein, if the low-pass filtered data array is produced in the k-space domain, it is transformed into the spatial image domain;

band-pass filter the data array, in at least one of

(a) the k-space domain or

(b) the spatial image domain of said image of patient anatomy,

to produce a band-pass filtered data array in the k-space domain or the spatial image domain;

wherein, if the band-pass filtered data array is produced in the k-space domain, it is transformed into the spatial image domain;

high-pass filter a data array, in at least one of

(a) the k-space domain or

(b) the spatial image domain of said image of patient anatomy,

to produce a high-pass filtered data array in the k-space domain or the spatial image domain;

wherein, if the high-pass filtered data array is produced in the k-space domain, it is transformed into the spatial image domain;

threshold and feather said band-pass filtered data array in the spatial image domain to produce an edge mask data array;

multiply said edge mask data array with said high-pass filtered data array in the spatial image domain; and

add the result of the multiplying to said low-pass filtered data array in the spatial image domain to produce a Gibbs' noise filtered image data array in the spatial image domain.

2. An MRI processor system as in claim 1 , wherein at least said band-pass filtering is performed in the k-space domain and then Fourier-Transformed to produce magnitude data for a respectively corresponding pass-band filtered data array in the spatial image domain, said band-pass filtering in k-space being performed using a filtering windowing function having omni-directionality in k-space.

3. An MRI processor system as in claim 1 , wherein at least said band-pass filtering is performed in the k-space domain and then Fourier-Transformed to produce magnitude data for a respectively corresponding pass-band filtered data array in the spatial image domain, said band-pass filtering in k-space being performed using a filtering windowing function that has either omni-directional or separate bidirectional filters corresponding to Canny-type image edge extractors.

4. An MRI processor system as in claim 1 , wherein:

said low-pass, band-pass and high-pass filtering are performed in the k-space domain and then two-dimensionally Fourier-Transformed to produce magnitude data for respectively corresponding filtered data arrays in the spatial image domain.

5. An MRI processor system as in claim 1 , wherein:

said low-pass and band-pass filtering are performed in the k-space domain and then two-dimensionally Fourier-Transformed to produce magnitude data for respectively corresponding low-pass and band-pass filtered data arrays in the spatial image domain.

6. An MRI processor system as in claim 3 , wherein:

said data arrays in the k-space domain are two-dimensional data arrays having P×Q array elements;

at least said low-pass and band-pass filtering is effected using respectively corresponding window filtering arrays that are each sized to substantially match the N×M size of the acquired raw k-space data array, or such array after basic preprocessing steps, being filtered, where N<P and M<Q; and

said high-pass filtering is effected using a respectively corresponding filtering windowing function that is sized to substantially match the size of a k-space array container having substantially only said N×M size data array therewithin, but otherwise having zero values or small values resulting from previous non-linear processing.

7. An MRI processor system as in claim 1 , wherein said high-pass filtered data array is soft thresholded in the spatial image domain to produce a soft thresholded high-pass filtered data array before multiplication with said edge mask data array.

8. An MRI processor system as in claim 1 in combination with an MRI gantry including a static field magnet, gradient field coils and at least one radio frequency (RF) coil defining an imaging volume and an MRI data acquisition sub-system configured to control said gradient field and RF coils, to store into said memory an N×M array of raw MRI data in k-space as said data array representing an image, wherein N equals an effective number of phase-encoding increments in a Gpe phase encoding dimension or a target dimension after partial Fourier or parallel imaging preprocessing and M equals an effective number of frequency-encoded samples obtained in a Gro read-out dimension or a target dimension after partial Fourier or data processing during an MRI data acquisition scan sequence.

9. An MRI processor system as in claim 1 , wherein said data arrays representing an image of patient anatomy stored in said memory are generated by inverse two-dimensional Fourier-Transformation of a digitized image of patient anatomy in the spatial image domain into the k-space domain where the data array stored in said memory is an N×M or P×Q array in k-space data representing said image of patient anatomy, where N<P and M<Q.