Quantification and imaging methods and system of the echo texture feature

• US 9,773,307 B2
• Filed: 12/02/2014
• Issued: 09/26/2017
• Est. Priority Date: 01/25/2010
• Status: Active Grant

• Current Assignee: Amcad Biomed Corporation
• Original Assignee: Amcad Biomed Corporation
• Inventors: Chang, King-Jen, Chen, Argon, Chen, Chiung-Nein, Chen, Kuen Yuan, Wang, Yu-Hsin, Huang, Kuo-Chen
• Primary Examiner(s): Bhatnagar, Anand
• Application Number:
  US14/558,298
• Publication Number:
  US 20150086095A1
• Time in Patent Office: 1,029 Days
• CPC Class Codes: G06T 2207/10132 Ultrasound image
• CPC Class Codes: G06T 2207/20104 Interactive definition of region of interest [ROI]
• CPC Class Codes: G06T 2207/30096 Tumor; Lesion
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/41 based on statistical description of texture

Abstract

The present invention provides quantification and imaging methods and a system of the echo-texture feature, comprising: obtaining an ultrasonic image; calculating all the pixel values in a selected ROI of the ultrasonic image to obtain a regional standard deviation; excluding pixels with a pixel value smaller than a multiple of the regional standard deviation in the selected ROI; counting a set of pixels centered around a N^th pixel to gather a N^th local mean, a N^th local variance and a N^th local coefficient of variance corresponding the set of pixel values, wherein N is from 1 to the number of the pixels remaining in the selected ROI; and obtaining an echo-texture index according to the local means, the local variances, or the local coefficient of variances. The imaging of echo texture which shows the echo texture distribution of the selected ROI with a color scale changing continuously from red to blue is also included. A parameter is provided to adjust the visualization enhancement of the echo texture.

Claims

1. A method for quantifying an echo texture feature, comprising:

obtaining an ultrasound image, wherein the ultrasound image comprises a plurality of pixels, wherein each pixel contains a pixel value;

defining a region of interests on the ultrasound image and determining a regional standard deviation, wherein the regional standard deviation is the standard deviation of the pixel values of the pixels in the selected ROI;

eliminating the pixels having the pixel value lower than a standard value in the selected ROI, wherein the standard value is a multiple of the regional standard deviation;

generating a set of local statistical parameters for each of the pixels remaining in the selected ROI, a N^th set of local statistical parameters is obtained from the pixel points within a local area composed of the N^th pixel point and the pixel points adjacent the N^th pixel in the selected ROI, and the N^th pixel is one of the pixels remaining in the selected ROI, N is a natural number from 1 to the number of the pixels remaining in the selected ROI; and

acquiring at least one echo texture index in accordance with the local statistical parameters.

2. The method as claimed in claim 1, wherein the local statistical parameters comprise a plurality of local coefficient of variances (local CVs), and the at least one echo texture index is a mean of the local CVs (MOCV).

3. The method as claimed in claim 1, wherein the local statistical parameters comprise a plurality of local means and local variances, and the at least one echo texture index is a result of Sqrt(VOV)/MOV, VOV represents the variance of the local variances and MOV represents the mean of the local variances.

4. The method as claimed in claim 1, wherein the local area of the pixels is covered by a k-by-k square matrix, k is a natural number.

5. A method for visualizing the echo texture feature, comprising:

obtaining an ultrasound image, wherein the ultrasound image comprises a plurality of pixels, wherein each pixel contains a pixel value;

defining a region of interests (ROI) on the ultrasound image and determining a regional standard deviation, wherein the regional standard deviation is the standard deviation of the pixel values of the pixels in the selected ROI;

eliminating the pixels having the pixel value lower than a standard value in the selected ROI, Wherein the standard value is a multiple of the regional standard deviation;

generating a set of local statistical parameters for each of the pixels remaining in the selected ROI, a N^th set of local statistical parameters is obtained from the pixels within a local area composed of the N^th pixel points and the pixel points adjacent the N^th pixel in the selected ROI, and the N^th pixel is one of the pixels remaining in the selected ROI, N is a natural number from 1 to the number of the pixels remaining in the region of interests, and the local statistical parameters comprises a plurality of local means; and

acquiring at least one echo texture index in accordance with the local statistical parameters;

generating a plurality of echo texture imaging intensities, wherein the each echo texture imaging intensity represents the absolute difference between a regional mean and the local mean of the pixels remaining in the region of interests, and wherein the regional mean is the mean of the pixel values of the pixels remaining in the selected ROI; and

illustrating a color scale image of echo texture feature in accordance with the at least one echo texture index and the echo texture imaging intensities.

6. The method as claimed in claim 5, further comprises the steps of:

comparing each echo texture imaging intensity to an upper limit and a lower limit; and

generating visualized values from the step of comparing, wherein each visualized value is generated by the following formula;

7. The method as claimed in claim 6, wherein the local statistical parameters comprises local variances and the method further comprises the steps of;

generating a regional standard deviation of the pixels remaining in the selected ROI;

transforming the local means and the local variances to a mean of the local variances (MOV) and a variance of the local variances (VOV); and

determining the upper limit and the lower limit, wherein the upper limit is determined by the following formula;

U=(MOV/VOV)×

(σ

′

)/(S₁),

and the lower limit is determined by the following formula;

L=(MOV/VOV)×

(σ

′

)/(S₂),

wherein U represents the upper limit, L represents the lower limit, MOV represents the mean of the local variances, VOV represents the variance of the local variances, σ

′

represents the regional standard deviation, S₁ represents an upper bound, and S₂ represents a lower bound.

8. The method as claimed in claim 7, wherein the upper bound and the lower bound are two adjustable factors, and both fall between 0.5 and 10.0, and wherein the lower bound is always greater than the upper bound.

9. The method as claimed in claim 6, wherein the local statistical para meters comprises local CVs and the method further comprises the steps of:

generating a regional standard deviation of the pixels remaining in the selected ROI;

transforming the local CVs to a mean of the local CV; and

determining the upper limit and the lower limit, wherein the upper limit is determined by the following formula;

U=(1/MOCV)×

(σ

′

)/(S₁),

and the lower is determined by the following formula;

L=(1/MOCV)×

(σ

′

)/(S₂),

wherein U represents the upper limit, L represents the lower limit, MOCV represents the mean of the local CVs, σ

′

represents the regional standard deviation, S₁ represents an upper bound, and S₂ represents a lower bound.

10. The method as claimed in claim 9, wherein the upper bound and the lower bound are two adjustable factors, and both fall between 0.5 and 10.0, and wherein the lower bound is always greater than the upper bound.

11. The method as claimed in claim 5, wherein the local area of the pixels is covered by a k-by-k square matrix, wherein k is a natural number.

12. A system for quantifying an echo texture feature, comprising:

an ultrasound image capture device is configured to acquire an ultrasound image, wherein the ultrasound image comprises a plurality of pixels and each pixel contains a pixel value;

an image processing module connects with the ultrasound image capture device is configured to receive and process the ultrasound images, wherein the image processing module further comprises an analysis unit and a processing unit connected to the analysis unit;

a display device connects with the image processing module is configured for display of the ultrasound images; and

an input device connects with the image processing module is configured to define a region of interests (ROI) on an ultrasound image;

wherein the analysis unit is configured to receive the selected ROI, and the processing unit is configured to determine a regional standard deviation of the pixel values of the pixels in the selected ROI;

wherein the analysis unit is further configured to eliminate pixels having the pixel value lower than a standard value, a multiple of the regional standard deviation, in the selected ROI, wherein the analysis unit is yet further configured to generate a set of local statistical parameters for each of the pixels remaining in the selected ROI, and a N^th set of local statistical parameters is obtained from the pixels within a local area composed of the N^th pixel point and the pixel points adjacent the N^th pixel in the selected ROI, and wherein the N^th pixel is one of the remaining pixels in the selected ROI, N is a natural number from 1 to the number of the pixels remaining in the selected ROI; and

wherein the processing unit is further configured to obtained at least one echo texture index based on the local statistical parameters.

13. The system as claimed in claim 12, wherein the local statistical parameters comprise a plurality of local coefficient of variances (local CVs), and wherein the at least one echo texture index is a mean of the local CVs (MOCV).

14. The system as claimed in claim 12, wherein the local statistical parameters comprise a plurality of local means and a plurality of local variances, and wherein the at least one echo texture index is the result of Sqrt(VOV)/MOV, and wherein VOV represents the variance of the local variances and MOV represents the mean of the local variances.

15. A system for visualizing an echo texture feature, comprising:

an ultrasound image capture device is configured to acquire an ultrasound image, wherein the ultrasound image comprises a plurality of pixels and each pixel contains a pixel value;

an image processing module connects with the ultrasound image capture device is configured to receive and process ultrasound images, wherein the image processing module further comprises an analysis unit and a processing unit connecting to the analysis unit;

a display device connects with the image processing module is configured for display of the ultrasound images; and

an input device connects with the image processing module is configured to define a region of interests (ROI) on an ultrasound image;

wherein the analysis unit is configured to receive the region of interests, and the processing unit is configured to determine a regional standard deviation of the pixel values of the pixels in the selected ROI;

wherein the analysis unit is further configured to eliminate the pixels having the pixel value lower than a standard value, a multiple of the regional standard deviation, in the selected ROI, wherein the analysis unit is yet further configured to generate a set of local statistical parameters for each of the pixels remaining in the selected ROI, a N^th set of the local statistical parameters is obtained from the pixels within a local area composed of the N^th pixel point and the pixel points adjacent the N^th pixel in the selected ROI, N is a natural number from 1 to the number of the pixels remaining in the selected ROI; and

wherein the processing unit is further configured to obtained at least one echo texture index based on the local statistical parameters, and wherein the processing unit is yet further configured to obtained echo texture imaging intensities based on the absolute differences between a regional mean and the local mean of each pixel, wherein the regional mean is a mean of the pixels remaining in the selected ROI; and

wherein the analysis unit is also configured to illustrate a color scale image of echo texture feature in accordance with the at least one echo texture index and the echo texture imaging intensities.

16. The system as claimed in claim 15, wherein the processing unit is further configured to compare each echo texture imaging intensity to an upper limit and a lower limit, and the processing unit is yet further configured to determine visualized values, and wherein each visualized value is determined by the following formula:

17. The system as claimed in claim 16, wherein the local statistical parameters comprises a plurality of local variances and the processing unit is further configured to generate a regional standard deviation of the pixels in the selected ROI and transform the local means and the local variances to a mean of the local variances (MOV) and a variance of the local variances (VOV), and the processing unit is yet further configured to determine the upper limit and the lower limit, wherein the upper limit is determined by the following formula:

U=(MOV/VOV)×

(σ

′

)/(S₁),

and the lower limit is determined by the following formula;

L=(MOV/VOV)×

(σ

′

)/(S₂),

wherein U represents the upper limit, L represents the lower limit, MOV represents the mean of the local variances, VOV represents the variance of the local variances, σ

′

represents the regional standard deviation, S₁ represents an upper bound, and S₂ represents a lower bound.

18. The system as claimed in claim 17, wherein the upper bound and the lower bound are two adjustable factors, and both fall between 0.5 and 10.0, and wherein the lower bound is always greater than the upper bound.

19. The system as claimed in claim 16, wherein the local statistical parameters comprises a plurality of local variances and the processing unit is further configured to generate a regional standard deviation of the pixels remaining in the selected ROI and transform the local CVs to a mean of the local CVs (MOCV), and the processing unit is yet further configured to determine the upper limit and the lower limit, wherein the upper limit is determined by the following formula:

U=(1/MOCV)×

(σ

′

)/(S₁),

and the lower limit is determined by the following formula;

L=(MOCV)×

(σ

′

)/(S₂),

wherein U represents the upper limit, L represents the lower limit, MOCV represents the mean of the local CVs, σ

′

represents the regional standard deviation, S₁ represents an upper bound, and S₂ represents a lower bound.

20. The system as claimed in claim 19, wherein the upper bound and the lower bound are two adjustable factors, and both fall between 0.5 and 10.0, and wherein the lower bound is always greater than the upper bound.