Computationally efficient noise reduction filter for enhancement of ultrasound images

• US 20030097069A1
• Filed: 07/17/2002
• Published: 05/22/2003
• Est. Priority Date: 11/21/2001
• 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: Avinash, Gopal B., Ghosh, Pinaki
• Granted Patent: US 6,592,523 B2
• Time in Patent Office: Days
• US Class Current: 600/447
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/20012 Locally adaptive
• CPC Class Codes: G06T 2207/20016 Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 5/002 Denoising; Smoothing noise processing or correction adapted to be used in an image pickup device containing and electronic image sensor H04N23/81, H04N25/60 - H04N25/67
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/70 Denoising; Smoothing

Abstract

In ultrasound imaging, acquired images are corrupted by slowly varying multiplicative non-uniformity. When the image is corrected for non-uniformity alone, noise in the dark regions of the original image becomes multiplicatively enhanced, thereby providing an unnatural look to the image. A pre-filtering technique is used to reduce noise in ultrasound pixel images by shrinking initial image data and processing the shrunken image with known segmentation-based filtering techniques that identify and differentially process structures within the image. The segmentation is based on both gradient threshold and the distance from the near field of the ultrasound image. This modification selectively suppresses near-field artifacts. After processing, the shrunken image is enlarged to the dimensions of the initial data and then blended with the initial image to form the final image. During blending, a small predetermined fraction of intensity-dependent, uniform random noise is added to the non-structure region pixels whose intensities are above a pre-specified intensity threshold, to mitigate ultrasound speckles while leaving non-echogenic regions undisturbed.

Claims

1. An ultrasound imaging system comprising a data acquisition system for acquiring acoustic data, an image processor for converting acoustic data into a set of pixel intensity values for each image, a display monitor for displaying images, and a computer programmed to perform the following steps:

(a) shrinking an initial image by a predetermined factor to produce a shrunken image;

(b) creating a first binary mask as a function of whether pixels of said shrunken image have gradients greater than a gradient threshold and locations more than a predetermined distance from a near field in said shrunken image;

(c) filtering pixels corresponding to structural components in said shrunken image in accordance with a first filtering algorithm, said structural components being identified by said first binary mask;

(d) filtering pixels corresponding to non-structural components in said shrunken image in accordance with a second filtering algorithm different than said first filtering algorithm, said non-structural components being identified by said first binary mask

(e) expanding said filtered image and said first binary mask by said predetermined factor to produce an expanded image and a first expanded binary mask;

(f) blending one or more selected regions of the expanded image with a corresponding region or regions of the initial image, said blending being a function of said first binary mask;

(g) adding uniform random noise to one or more selected echogenic nonstructural regions of the expanded image; and

(h) outputting a final image to said display monitor, said final image being derived by performing at least steps (a) through (h).

2. The system as recited in claim 1, wherein said blending step comprises blending one or more selected structural regions of the expanded image with a corresponding region or regions of the initial image

3. The system as recited in claim 1, wherein said blending step comprises blending one or more selected non-structural regions of the expanded image with a corresponding region or regions of the initial image

4. The system as recited in claim 2, wherein said blending step further comprises blending one or more selected non-structural regions of the expanded image with a corresponding region or regions of the initial image

5. The system as recited in claim 1, further comprising the following steps:

creating a second binary mask as a function of whether pixels of said shrunken image have gradients greater than said gradient threshold and intensities greater than a predetermined intensity level; and

expanding said second binary mask by said predetermined factor to produce a second expanded binary mask,

wherein uniform random noise is added as a function of said second binary mask.

6. The system as recited in claim 5, wherein the amount of noise added is less than 5% of the intensity of a filtered pixel.

7. The system as recited in claim 1, wherein said step of shrinking is accomplished using a sub-sampling technique.

8. The system as recited in claim 7, wherein said sub-sampling technique comprises the step of pixel averaging in a kernel.

9. The system as recited in claim 1, wherein said first filtering algorithm comprises an orientation smoothing function that is performed only on structure pixels.

10. The system as recited in claim 9, wherein said first filtering algorithm further comprises an orientation sharpening function that is performed only on orientation-filtered structure pixels that have gradients above a pre-specified limit.

11. The system as recited in claim 1, wherein said second filtering algorithm comprises iteratively low-pass filtering the non-structure regions with a kernel.

12. The system as recited in claim 1, wherein said step of expanding is accomplished using interpolation.

13. The system as recited in claim 12, wherein said filtered image is expanded using bicubic interpolation and said first binary mask is expanded using bilinear interpolation.

14. The system as recited in claim 1, wherein said blending step is performed with different proportions for different selected regions.

15. A method for filtering an ultrasound image, comprising the following steps:

(a) shrinking an initial image by a, predetermined factor to produce a shrunken image;

(b) creating a first binary mask as a function of whether pixels of said shrunken image have gradients greater than a gradient threshold and locations more than a predetermined distance from a near field in said shrunken image;

(c) filtering pixels corresponding to structural components in said shrunken image in accordance with a first filtering algorithm, said structural components being identified by said first binary mask;

(d) filtering pixels corresponding to non-structural components in said shrunken image in accordance with a second filtering algorithm different than said first filtering algorithm, said non-structural components being identified by said first binary mask

(e) expanding said filtered image and said first binary mask by said predetermined factor to produce an expanded image and a first expanded binary mask;

(f) blending one or more selected regions of the expanded image with a corresponding region or regions of the initial image, said blending being a function of said first binary mask; and

(g) adding uniform random noise to one or more selected echogenic nonstructural regions of the expanded image to form a final image suitable for display or further image enhancement.

16. The method as recited in claim 15, further comprising the following steps:

creating a second binary mask as a function of whether pixels of said shrunken image have gradients greater than said gradient threshold and intensities greater than a predetermined intensity level; and

expanding said second binary mask by said predetermined factor to produce a second expanded binary mask,

wherein uniform random noise is added as a function of said second binary mask.

17. The method as recited in claim 16, wherein the amount of noise added is less than 5% of the intensity of a filtered pixel.

18. The method as recited in claim 15, wherein said first filtering algorithm comprises an orientation smoothing function that is performed only on structure pixels.

19. The method as recited in claim 18, wherein said first filtering algorithm further comprises an orientation sharpening function that is performed only on orientation-filtered structure pixels-that have gradients above a pre-specified limit.

20. The method as recited in claim 15, wherein said second filtering algorithm comprises iteratively low-pass filtering the non-structure regions with a kernel.

21. The method as recited in claim 15, wherein said step of expanding is accomplished using interpolation. said filtered image being expanded using bicubic interpolation and said first binary mask being expanded using bilinear interpolation.

22. The method as recited in claim 15, wherein said blending step is performed with different proportions for different selected regions.

23. An ultrasound image filter comprising:

means for shrinking an initial image by a predetermined factor to produce a shrunken image;

means for orientation smoothing pixels corresponding to structural components in said shrunken image;

means for iteratively low-pass filtering pixels corresponding to non-structural components in said shrunken image;

means for expanding said filtered image by said predetermined factor to produce an expanded image;

means for blending one or more selected regions of the expanded image with a corresponding region or regions of the initial image, said blending being a function of whether the corresponding pixel of said shrunken image has a gradient greater than a gradient threshold and a location more than a predetermined distance from a near field in said shrunken image; and

means for adding uniform random noise to one or more selected echogenic non-structural regions of the expanded image to form a final image suitable for display or further image enhancement.

24. The filter as recited in claim 23, further comprising:

means for creating a binary mask as a function of whether pixels of said shrunken image have gradients greater than said gradient threshold and intensities greater than a predetermined intensity level; and

means for expanding said binary mask by said predetermined factor to produce an expanded binary mask,

wherein said means for adding uniform random noise adds noise as a function of said binary mask.

25. The filter as recited in claim 24, wherein the amount of noise added is less than 5% of the intensity of a filtered pixel.

26. A method for filtering an ultrasound image, comprising the following steps:

shrinking an initial image by a predetermined factor to produce a shrunken image;

orientation smoothing pixels corresponding to structural components in said shrunken image;

iteratively low-pass filtering pixels corresponding to non-structural components in said shrunken image;

expanding said filtered image by said predetermined factor to produce an expanded image;

blending one or more selected regions of the expanded image with a corresponding region or regions of the initial image, said blending being a function of whether the corresponding pixel of said shrunken image has a gradient greater than a gradient threshold and a location more than a predetermined distance from a near field in said shrunken image; and

adding uniform random noise to one or more selected echogenic non-structural regions of the expanded image to form a final image suitable for display or further image enhancement.

27. A method for mitigating speckle in an ultrasound image, comprising the following steps:

creating a binary mask having a first value binary value for each pixel of an image that satisfies a first condition of having a gradient greater than a gradient threshold and a second condition of having an intensity greater than a predetermined intensity level, and a second binary value for each pixel that does not meet both said first and second conditions; and

adding uniform random noise to each pixel of said image that corresponds to a pixel in said binary mask having said first binary value and not adding noise to other pixels of said image.

28. An ultrasound imaging system comprising a data acquisition system for acquiring acoustic data, an image processor for converting acoustic data into a set of pixel intensity values for each image, a display monitor for displaying images, and a computer programmed to perform the following steps:

(a) creating a binary mask having a first value binary value for each pixel of an image that satisfies a first condition of having a gradient greater than a gradient threshold and a second condition of having an intensity greater than a predetermined intensity level, and a second binary value for each pixel that does not meet both said first and second conditions;

(b) adding uniform random noise to each pixel of said image that corresponds to a pixel in said binary mask having said first binary value and not adding noise to other pixels of said image; and

(c) outputting a final image to said display monitor, said final image being derived by performing at least steps (a) and (b).