IMAGE PROCESSING METHOD AND X-RAY CT SYSTEM

• US 20070058883A1
• Filed: 09/14/2006
• Published: 03/15/2007
• Est. Priority Date: 09/15/2005
• Status: Active Grant

• Current Assignee: GE Medical Systems Global Technology Company LLC (GE Healthcare Technologies, Inc.)
• Original Assignee: GE Medical Systems Global Technology Company LLC (GE Healthcare Technologies, Inc.)
• Inventors: Xing, Zhanfeng
• Granted Patent: US 7,668,360 B2
• Time in Patent Office: Days
• US Class Current: 382/275
• CPC Class Codes: A61B 6/583 using calibration phantoms
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/20064 Wavelet transform [DWT]
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 5/10 using non-spatial domain filtering
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 5/73 Deblurring; Sharpening
• CPC Class Codes: G06T 7/13 Edge detection

Abstract

An object of the present invention is to provide an image processing method for reducing noises without causing a side effect and an X-ray CT system that performs the image processing. An input image is wavelet-transformed using a gradient form. Resultant wavelet vectors are classified into categories of strongly edged objects, weakly edged objects, radial lines, and noises. The wavelet vectors classified into the category of strongly edged object are left intact. The wavelet vectors classified into the category of weakly edged objects have the directions thereof filtered. The wavelet vectors classified into the categories of radial lines and noises are smoothed. The resultant wavelet vectors are inverse-wavelet-transformed in order to produce an output image.

Claims

1. An image processing method comprising the steps of:

wavelet-transforming an input image using a gradient form;

classifying resultant wavelet vectors into categories of strongly edged objects, weakly edged objects, radial lines, and noises;

leaving the wavelet vectors, which are classified into the category of strongly edged objects, intact;

filtering the directions of the wavelet vectors classified into the category of weakly edged objects;

smoothing the wavelet vectors classified into the categories of radial lines and noises; and

inverse-wavelet-transforming the resultant wavelet vectors so as to produce an output image.

2. The image processing method according to claim 1, wherein:

the classification employs a first threshold concerning the magnitude of a vector, a second threshold smaller than the first threshold, and a third threshold concerning the regulation in the direction of a vector;

wavelet vectors whose magnitudes are larger than the first threshold are classified into the category of strongly edged objects;

wavelet vectors whose magnitudes are equal to or smaller than the first threshold and larger than the second threshold and whose regulations in directions thereof are larger than the third threshold are classified into the category of weakly edged objects;

wavelet vectors whose magnitudes are equal to or smaller than the first threshold and whose regulations in directions thereof are equal to or smaller than the third threshold are classified into the category of radial lines; and

wavelet vectors whose magnitudes are equal to or smaller than the second threshold are classified into the category of noises.

3. The image processing method according to claim 2, wherein the regulation in the direction of a vector is expressed as a ratio of a mean vector, which is a mean of a center vector located in the center of a window defined with a matrix of 3 by 3 and two ambient vectors whose differences from the center vector are the smallest, to a mean vector that is a mean of all vectors in the window.

4. The image processing method according to claim 1, wherein the filtering of directions is achieved by sampling a combination of a center vector located in the center of a window defined with a matrix of 3 by 3 and two ambient vectors the sum of whose differences from the center vector is the smallest, and replacing the center vector with a mean vector that is a mean of the two ambient vectors and the center vector.

5. The image processing method according to claim 1, wherein the smoothing of vectors is achieved by replacing a center vector, which is located in the center of a window defined with a matrix of 3 by 3, with a mean vector that is a mean of all vectors in the window.

6. An X-ray CT system comprising a data acquisition means for acquiring data by scanning a subject with X-rays, an image reconstruction means for reconstructing an image on the basis of the acquired data, and an image processing means for processing the reconstructed image, wherein:

the image processing means comprises;

a transforming means for wavelet-transforming an input image using a gradient form;

a classifying means for classifying resultant wavelet vectors into categories of strongly edged objects, weakly edged objects, radial lines, and noises;

leaving the wavelet vectors, which are classified into the category of strongly edged objects, intact;

filtering the directions of the wavelet vectors classified into the category of weakly edged objects;

smoothing the wavelet vectors classified into the categories of radial lines and noises; and

inverse-wavelet-transforming the resultant wavelet vectors so as to produce an output image.

7. The X-ray CT system according to claim 6, wherein:

the classification employs a first threshold concerning the magnitude of a vector, a second threshold smaller than the first threshold, and a third threshold concerning the regulation in the direction of a vector;

wavelet vectors whose magnitudes are larger than the first threshold are classified into the category of strongly edged objects;

wavelet vectors whose magnitudes are equal to or smaller than the first threshold and larger than the second threshold and whose regulations in directions thereof are larger than the third threshold are classified into the category of weakly edged objects;

wavelet vectors whose magnitudes are equal to or smaller than the first threshold and whose regulations in directions thereof are equal to or smaller than the third threshold are classified into the category of radial lines; and

wavelet vectors whose magnitudes are equal to or smaller than the second threshold are classified into the category of noises.

8. The X-ray CT system according to claim 7, wherein the regulation in the direction of a vector is expressed as a ratio of a mean vector, which is a mean of a center vector located in the center of a window defined with a matrix of 3 by 3 and two ambient vectors whose differences from the center vector are the smallest, to a mean vector that is a mean of all vectors in the window.

9. The X-ray CT system according to claims 6, wherein the filtering of directions is achieved by sampling a combination of a center vector, which is located in the center of a window defined with a matrix of 3 by 3, and two ambient vectors the sum of whose differences from the center vector is the smallest, and replacing the center vector with a mean vector that is a mean of the two ambient vectors and the center vector.

10. The X-ray CT system according to any of claims 6, wherein the smoothing of vectors is achieved by replacing a center vector, which is located in the center of a window defined with a matrix of 3 by 3, with a mean vector that is a mean of all vectors in the window.