CN109360173A - Color Doppler Flow Imaging based on improved variance is as noise-reduction method - Google Patents
Color Doppler Flow Imaging based on improved variance is as noise-reduction method Download PDFInfo
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- CN109360173A CN109360173A CN201811402819.5A CN201811402819A CN109360173A CN 109360173 A CN109360173 A CN 109360173A CN 201811402819 A CN201811402819 A CN 201811402819A CN 109360173 A CN109360173 A CN 109360173A
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- blood flow
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- flow velocity
- variance
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- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000003384 imaging method Methods 0.000 title claims abstract description 8
- 230000017531 blood circulation Effects 0.000 claims abstract description 48
- 238000006073 displacement reaction Methods 0.000 claims abstract description 9
- 230000002194 synthesizing effect Effects 0.000 claims abstract description 4
- 238000005111 flow chemistry technique Methods 0.000 claims description 8
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 238000012935 Averaging Methods 0.000 claims description 2
- 238000011946 reduction process Methods 0.000 claims description 2
- 230000000004 hemodynamic effect Effects 0.000 claims 1
- 239000008280 blood Substances 0.000 abstract description 6
- 210000004369 blood Anatomy 0.000 abstract description 6
- 238000010586 diagram Methods 0.000 description 6
- 238000001914 filtration Methods 0.000 description 6
- 230000015572 biosynthetic process Effects 0.000 description 3
- 238000003786 synthesis reaction Methods 0.000 description 3
- 230000000052 comparative effect Effects 0.000 description 2
- 238000000354 decomposition reaction Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 210000000554 iris Anatomy 0.000 description 1
- 238000002604 ultrasonography Methods 0.000 description 1
Classifications
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- G06T5/70—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10132—Ultrasound image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
- G06T2207/30104—Vascular flow; Blood flow; Perfusion
Abstract
A kind of Color Doppler Flow Imaging based on improved variance is as noise-reduction method, by during the velocity measuring that color doppler image is handled, carrying out space variance update processing to blood flow velocity signal graph to be optimized and obtaining updated blood flow velocity signal graph for synthesizing with B image；Wherein space variance update processing is that characteristic value of the diagonal displacement variance of after image block as image block center pixel is calculated after being updated using Moving Window to each image block in blood flow velocity signal graph to be optimized, for judging whether the pixel is noise.The present invention can filter out random velocity noise and micro- blood echo under minimal energy intensity is clearly showed that.
Description
Technical field
The present invention relates to a kind of technology of field of medical device, specifically a kind of colour based on improved variance is more
General Le blood-stream image noise-reduction method.
Background technique
It is smaller that micro- blood echo signal can occur when observing micro- blood flow for color Doppler imaging, the feelings vulnerable to interference
Condition.Main interfere derives from random noise, and current space time filtering algorithm, can not all do to random velocity noise
It effectively filters out, i.e., after wall filtering and Conventional spatial filtering/time filtering have been handled, can also remain random velocity noise.To
Occur more noises while image section is strengthened after causing gain to be turned up and reduce picture quality (Fig. 3 a).
Since random noise exists, distribution is random, focus mostly in high-speed region, noise energy distribution is more concentrated and noise
The features such as there is no relevances is distributed on the forward and backward frame of doppler image, and existing Variance Method is when crossing noise filtering
Also the micro- blood echo signal for being very easy to for energy being on close level filters together.
Summary of the invention
The present invention In view of the above shortcomings of the prior art, proposes a kind of color Doppler blood based on improved variance
Stream picture noise-reduction method can filter out random velocity noise and enable micro- blood echo under minimal energy intensity clearly aobvious
Show.
The present invention is achieved by the following technical solutions:
The present invention is by during the velocity measuring that color doppler image is handled, to blood flow velocity signal graph to be optimized
Space variance is carried out to update processing and obtain updated blood flow velocity signal graph for synthesizing with B image.
The space variance update processing refers to: using Moving Window to each figure in blood flow velocity signal graph to be optimized
Characteristic value of the diagonal displacement variance of after image block as image block center pixel is calculated after being updated as block, for sentencing
Whether the pixel of breaking is noise.
The space variance update processing, carries out feature to each pixel in blood flow velocity signal graph to be optimized one by one
The calculating of value and noise judgement, to obtain updated blood flow velocity signal graph.
Detailed description of the invention
Fig. 1 is color Doppler B ultrasound Irnaging procedures schematic diagram；
Fig. 2 is that embodiment deals with objects schematic diagram；
In figure: a is random noise image, and b is the blood flow velocity signal graph comprising blood flow and velocity information, and c is comparative example
Schematic diagram；
Fig. 3 is embodiment effect comparison schematic diagram；
In figure: a is conventional images, and b is image after this method processing；
Fig. 4 is embodiment Moving Window processing schematic；
In figure: a is image, and b is original picture block, and c is image block after movement.
Specific embodiment
As shown in Figure 1, being Color Doppler Flow Imaging as noise reduction system, include: decomposition unit, B image processing unit, blood
Stream processing unit, scan conversion unit and color image synthesis unit, in which: decomposition unit is by the i/q signal from demodulator
It is exported respectively to B image processing unit and blood flow processing unit, B image processing unit is through envelope detection, compression enhancing and remaining
Black and white B image is exported to scan conversion unit after brightness processing, blood flow processing unit is through wall filtering, auto-correlation, detection filter processing
Backward scan conversion unit output blood flow velocity signal graph and blood flow energy signal, scan conversion unit will according to default resolution ratio
Adjacent several frame images merge after superposition processing output to color image synthesis unit, color image synthesis unit according to
Blood flow velocity signal graph and blood flow energy signal generate color doppler image.
The present embodiment is related to a kind of Color Doppler Flow Imaging as noise reduction module, is set to blood flow processing unit and scanning becomes
It changes between unit, further noise reduction process is carried out to the blood flow velocity signal graph of blood flow processing unit output, which includes:
Moving Window processing unit, variance updating unit and noise judging unit, in which: Moving Window processing unit is defeated from blood flow processing unit
Interception image block is recycled in blood flow velocity signal graph out and is exported to variance updating unit, and variance updating unit will be calculated
The diagonal displacement variance of image block export to noise judging unit, noise judging unit feeds back to judging result at Moving Window
Reason unit simultaneously generates updated blood flow velocity signal graph.
During the present embodiment is by the velocity measuring that handles in above-mentioned color doppler image, to blood flow velocity to be optimized
Signal graph carries out space variance and updates processing and obtain updated blood flow velocity signal graph for synthesizing with B image.
The space variance update processing refers to: using Moving Window to each figure in blood flow velocity signal graph to be optimized
Characteristic value of the diagonal displacement variance of after image block as image block center pixel is calculated after being updated as block, for sentencing
Whether the pixel of breaking is noise.
As shown in figure 4, the image block update refers to: using Moving Window in blood flow velocity signal graph to be optimized (as schemed
Original image block I is selected in 4a)0(such as Fig. 4 b) and to the right and downwards each movement one pixel, to obtain new images I1(as schemed
4c), then with I0-I1As updated image block.
The side length of Moving Window in the present embodiment is 3 pixels, in other cases according to the speed speed of test object,
The size of Moving Window can increase accordingly.
According to different applications or test object, which can also be further expanded to move more pictures
Element is mobile to other directions.
The diagonal displacement variance refers to: it calculates in updated image block and is averaging after the quadratic sum of each pixel,
I.e.Wherein: N is number of pixels, and i, j are respectively the row, column number and i, j >=1 of opposite original image block.
As shown in figures 4 a and 4b, the diagonal displacement variance is as original image block I0With the characteristic value of center pixel,
When the center pixel is located at the vertex of image, image block is filled by the way of center pixel duplication, is then treated excellent
Change calculating and noise judgement that each pixel in blood flow velocity signal graph carries out characteristic value one by one, to obtain updated blood
Flow velocity degree signal graph.
The judgement refers to: being compared using characteristic threshold value with the characteristic value of each pixel, when characteristic value is greater than spy
The pixel is then determined as noise and modifies pixel value when levying threshold value, to obtain updated blood flow velocity signal graph.
When being determined as noise, using but be not limited to the pixel value zero setting otherwise retaining blood flow velocity signal graph to be optimized
On pixel value.
The characteristic threshold value includes:
I) multiple regions are divided into according to the distribution of each pixel of image, each region uses threshold independent
Value, or
Ii) using in image in all pixels the average value of the smallest partial pixel as global threshold.
As shown in Figure 2 a be random noise figure, Fig. 2 b be comprising the blood flow velocity signal graph comprising blood flow and velocity information,
Fig. 2 c is the comparative diagram with line of demarcation.Fig. 2 a~c is handled according to the algorithm of standard variance will obtain it is identical
Filter result.The oriented information in part i.e. in Fig. 2 b and Fig. 2 c will be considered as noise and filter out together, and be calculated using this method
To Fig. 2 a in random noise variance be much larger than existing standard variance and Fig. 2 b and Fig. 2 c, to facilitate subsequent filter
Removal.As shown in Figure 3b, the effect diagram as obtained after the above method is handled irises out part in Fig. 3 a as can be seen
Random noise obtain significantly filter out and embodied clearly blood flow signal.
Above-mentioned specific implementation can by those skilled in the art under the premise of without departing substantially from the principle of the invention and objective with difference
Mode carry out local directed complete set to it, protection scope of the present invention is subject to claims and not by above-mentioned specific implementation institute
Limit, each implementation within its scope is by the constraint of the present invention.
Claims (10)
1. a kind of Color Doppler Flow Imaging based on improved variance is as noise-reduction method, which is characterized in that by more in colour
During the general velocity measuring for strangling image procossing, space variance update processing is carried out to blood flow velocity signal graph to be optimized and is obtained
Updated blood flow velocity signal graph with B image for synthesizing；
The space variance update processing refers to: using Moving Window to each image block in blood flow velocity signal graph to be optimized
Characteristic value of the diagonal displacement variance of after image block as image block center pixel is calculated after being updated, for judging this
Whether pixel is noise.
2. according to the method described in claim 1, it is characterized in that, the described image block update refers to: using Moving Window to excellent
Change in blood flow velocity signal graph and selects original image block I0With image block I after movement1, with I0-I1As updated image block.
3. according to the method described in claim 2, it is characterized in that, the movement refers to: either into eight directions to
At least one mobile pixel simultaneously obtains image block I1。
4. according to the method in claim 2 or 3, characterized in that when the center pixel is located at the vertex of image, image block
It is filled by the way of center pixel duplication, then each pixel in blood flow velocity signal graph to be optimized is carried out one by one
The calculating of characteristic value and noise judgement, to obtain updated blood flow velocity signal graph.
5. according to the method described in claim 1, it is characterized in that, the diagonal displacement variance refers to: calculating updated figure
As pixel each in block quadratic sum after be averaging, i.e.,Wherein: N is number of pixels, and i, j are respectively phase
To the row, column number and i, j of original image block >=1.
6. according to the method described in claim 1, it is characterized in that, the described space variance update processing, to Hemodynamic environment to be optimized
Each pixel in degree signal graph carries out the calculating and noise judgement of characteristic value one by one, to obtain updated blood flow velocity letter
Number figure.
7. according to the method described in claim 1, it is characterized in that, the judgement refers to: using characteristic threshold value and each pixel
Characteristic value be compared, the pixel be then determined as noise and modify pixel value when characteristic value is greater than characteristic threshold value, thus
Obtain updated blood flow velocity signal graph.
8. according to the method described in claim 7, it is characterized in that, be determined as the pixel value zero setting of noise, otherwise retain to be optimized
Pixel value on blood flow velocity signal graph.
9. according to the method described in claim 7, it is characterized in that, the characteristic threshold value includes:
I) multiple regions being divided into according to the distribution of each pixel of image, each region uses threshold value independent, or
Ii) using in image in all pixels the average value of the smallest partial pixel as global threshold.
10. a kind of Color Doppler Flow Imaging for realizing any of the above-described claim the method is as noise reduction module, feature exists
In, be set between blood flow processing unit and scan conversion unit, to blood flow processing unit output speed signal image carry out
Further noise reduction process, the module include: Moving Window processing unit, variance updating unit and noise judging unit, in which: are moved
Dynamic window processing unit recycles interception image block from the blood flow velocity signal graph that blood flow processing unit exports and exports to variance more
New unit, variance updating unit export the diagonal displacement variance for the image block being calculated to noise judging unit, and noise is sentenced
Judging result is fed back to Moving Window processing unit and generates updated blood flow velocity signal graph by disconnected unit.
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Cited By (1)
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| CN111714157A (en) * | 2020-07-24 | 2020-09-29 | 武汉中旗生物医疗电子有限公司 | Doppler ultrasonic blood flow automatic identification method and device |
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| CN108205814A (en) * | 2016-12-19 | 2018-06-26 | 中国科学院苏州纳米技术与纳米仿生研究所 | The black and white contour generating method of coloured image |
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