CN109360173B - Color Doppler blood flow image noise reduction method based on improved variance - Google Patents
Color Doppler blood flow image noise reduction method based on improved variance Download PDFInfo
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Abstract
A color Doppler blood flow image noise reduction method based on improved variance is characterized in that in the speed detection process of color Doppler image processing, a blood flow velocity signal diagram to be optimized is subjected to spatial variance updating processing, and the updated blood flow velocity signal diagram is obtained and used for being synthesized with an image B; the spatial variance updating process is to use a moving window to update each image block in the blood flow velocity signal diagram to be optimized, and then calculate the diagonal displacement variance of the updated image block as the characteristic value of the central pixel of the image block, so as to judge whether the pixel is noise or not. The invention can filter random speed noise so that the micro blood flow echo under extremely low energy intensity can be clearly displayed.
Description
Technical Field
The invention relates to a technology in the field of medical equipment, in particular to a color Doppler blood flow image noise reduction method based on improved variance.
Background
The color doppler imaging technique is prone to interference due to small micro blood flow echo signals when observing micro blood flow. The main interference is derived from random noise, but the current space/time filtering algorithm cannot effectively filter the random speed noise, namely, the random speed noise is remained after wall filtering and conventional space filtering/time filtering. Resulting in the enhancement of the image portion after the gain adjustment while more noise appears and degrading the image quality (fig. 3 a).
Because random noise exists and is distributed randomly, mostly concentrated in a high-speed area, noise energy is distributed more intensively, and noise distribution does not have relevance on a front frame and a rear frame of a Doppler image, the existing variance method is very easy to filter the micro blood flow echo signals with close energy levels when filtering noise.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an improved variance-based color Doppler blood flow image noise reduction method, which can filter random velocity noise so that micro blood flow echoes under extremely low energy intensity can be clearly displayed.
The invention is realized by the following technical scheme:
in the speed detection process of color Doppler image processing, the invention performs spatial variance updating processing on the blood flow speed signal diagram to be optimized and obtains an updated blood flow speed signal diagram for synthesizing with the B image.
The spatial variance updating processing comprises the following steps: and after each image block in the blood flow velocity signal diagram to be optimized is updated by adopting a moving window, calculating the diagonal displacement variance of the updated image block as the characteristic value of the central pixel of the image block, and judging whether the pixel is noise or not.
And the spatial variance updating process is used for calculating the characteristic value and judging the noise of each pixel in the blood flow velocity signal diagram to be optimized one by one so as to obtain an updated blood flow velocity signal diagram.
Drawings
FIG. 1 is a schematic flow chart of color Doppler B-mode ultrasound imaging;
FIG. 2 is a schematic diagram of an embodiment process object;
in the figure: a is a random noise image, b is a blood flow velocity signal diagram containing blood flow and velocity information, and c is a comparative example schematic diagram;
FIG. 3 is a schematic diagram showing comparison of effects of the embodiments;
in the figure: a is the existing image, b is the image processed by the method;
FIG. 4 is a diagram of an embodiment moving window process;
in the figure: a is an image, b is an original image block, and c is a moved image block.
Detailed Description
As shown in fig. 1, the system for reducing noise of color doppler blood flow image comprises: decomposition unit, B image processing unit, blood flow processing unit, scan conversion unit and color image synthesis unit, wherein: the decomposition unit respectively outputs I/Q signals from the demodulator to a B image processing unit and a blood flow processing unit, the B image processing unit outputs a black-and-white B image to the scanning conversion unit after envelope detection, compression enhancement and afterglow processing, the blood flow processing unit outputs a blood flow velocity signal diagram and a blood flow energy signal to the scanning conversion unit after wall filtering, autocorrelation and detection filtering processing, the scanning conversion unit combines and superposes a plurality of adjacent frame images according to preset resolution and outputs the combined images to the color image synthesis unit, and the color image synthesis unit generates a color Doppler image according to the blood flow velocity signal diagram and the blood flow energy signal.
The embodiment relates to a color Doppler blood flow image noise reduction module, which is arranged between a blood flow processing unit and a scan conversion unit, and is used for further noise reduction processing on a blood flow velocity signal diagram output by the blood flow processing unit, and the module comprises: a moving window processing unit, a variance updating unit and a noise judging unit, wherein: the moving window processing unit circularly intercepts image blocks from the blood flow velocity signal diagram output by the blood flow processing unit and outputs the image blocks to the variance updating unit, the variance updating unit outputs the calculated diagonal displacement variance of the image blocks to the noise judging unit, and the noise judging unit feeds back the judgment result to the moving window processing unit and generates an updated blood flow velocity signal diagram.
In the present embodiment, in the velocity detection process of the color doppler image processing, the spatial variance update processing is performed on the blood flow velocity signal diagram to be optimized, and the updated blood flow velocity signal diagram is obtained for being synthesized with the B image.
The spatial variance updating processing comprises the following steps: and after each image block in the blood flow velocity signal diagram to be optimized is updated by adopting a moving window, calculating the diagonal displacement variance of the updated image block as the characteristic value of the central pixel of the image block, and judging whether the pixel is noise or not.
As shown in fig. 4, the image block update refers to: selecting an original image block I in a blood flow velocity signal diagram to be optimized (as shown in FIG. 4a) by adopting a moving window0(see fig. 4b) and moving one pixel to the right and down, respectively, to obtain a new image I1(see FIG. 4c), then with I0-I1As an updated image block.
The side length of the moving window in this embodiment is 3 pixels, and the size of the moving window can be increased correspondingly according to the speed of the detected object in other occasions.
Depending on the application or the object to be detected, the moving pixels may be further expanded to move more pixels or move in other directions.
The diagonal displacement variance refers to: calculating the sum of squares of the individual pixels in the updated image block and averaging, i.e.
Wherein: n is the number of pixels, i and j are the numbers of rows and columns corresponding to the original image block respectively, and i and j are more than or equal to 1.
As shown in FIG. 4a and FIG. 4b, the variance of the diagonal shift is used as the original image block I0And filling the image blocks by adopting a central pixel copying mode according to the characteristic value of the central pixel when the central pixel is positioned at the top point of the image, and then calculating the characteristic value and judging the noise of each pixel in the blood flow velocity signal diagram to be optimized one by one so as to obtain an updated blood flow velocity signal diagram.
The judgment means that: and comparing the characteristic threshold with the characteristic value of each pixel, and judging the pixel as noise and modifying the pixel value when the characteristic value is greater than the characteristic threshold, thereby obtaining an updated blood flow velocity signal diagram.
When the noise is judged, the pixel value is set to be zero, otherwise, the pixel value on the blood flow velocity signal image to be optimized is reserved.
The characteristic threshold comprises:
i) dividing the image into a plurality of regions according to the distribution of each pixel, each region using a respective independent threshold value, or
ii) taking the average value of the smallest partial pixel in all pixels in the image as a global threshold value.
Fig. 2a shows a random noise map, fig. 2b shows a blood flow velocity signal map including information on blood flow and velocity, and fig. 2c shows a map with boundaries. Processing figures 2 a-c according to a standard deviation algorithm will result in exactly the same filtering result. That is, the local directional information in fig. 2b and fig. 2c is regarded as noise and filtered, and the variance of the random noise in fig. 2a calculated by the method is much larger than the standard variance in the prior art and fig. 2b and fig. 2c, so that subsequent filtering and removal are facilitated. As shown in fig. 3b, which is a schematic diagram of the effect obtained after the processing by the above method, as shown in fig. 3a, the random noise at the circled portion is largely filtered out and a clear blood flow signal is shown.
The foregoing embodiments may be modified in many different ways by those skilled in the art without departing from the spirit and scope of the invention, which is defined by the appended claims and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (7)
1. A color Doppler blood flow image noise reduction method based on improved variance is characterized in that in the speed detection process of color Doppler image processing, the spatial variance updating processing is carried out on a blood flow speed signal diagram to be optimized, and the updated blood flow speed signal diagram is obtained and used for being synthesized with an image B;
the spatial variance updating processing comprises the following steps: updating each image block in the blood flow velocity signal diagram to be optimized by adopting a moving window, and then calculating the diagonal displacement variance of the updated image block as the characteristic value of a central pixel of the image block to judge whether the pixel is noise or not;
the image block updating means that: selecting an original image block from a blood flow velocity signal diagram to be optimized by adopting a moving windowI 0And shifting, i.e. shifting at least one pixel in any of eight directions and obtaining an image blockI 1To do so byI 0-I 1As an updated image block;
the diagonal displacement variance refers to: calculating the sum of squares of the individual pixels in the updated image block and averaging, i.e.
Wherein: n is the number of the pixels,i、jrespectively the number of rows and columns relative to the original image blocki、j≥1。
2. The method as claimed in claim 1, wherein when the central pixel is located at the vertex of the image, the image block is filled by copying the central pixel, and then the feature value calculation and the noise judgment are performed one by one for each pixel in the blood flow velocity signal diagram to be optimized, thereby obtaining the updated blood flow velocity signal diagram.
3. The method according to claim 1, wherein the spatial variance updating process performs feature value calculation and noise judgment on each pixel in the blood velocity signal map to be optimized one by one, thereby obtaining an updated blood velocity signal map.
4. The method of claim 1, wherein said determining comprises: and comparing the characteristic threshold with the characteristic value of each pixel, and judging the pixel as noise and modifying the pixel value when the characteristic value is greater than the characteristic threshold, thereby obtaining an updated blood flow velocity signal diagram.
5. The method of claim 4, wherein the pixel values determined to be noise are zeroed, otherwise the pixel values on the blood flow velocity signal map to be optimized are retained.
6. The method of claim 4, wherein said characteristic threshold comprises:
i) dividing the image into a plurality of regions according to the distribution of each pixel, each region using a respective independent threshold value, or
ii) taking the average value of the smallest partial pixel in all pixels in the image as a global threshold value.
7. A color doppler flow image noise reduction system, comprising: blood flow processing unit, scan conversion unit, color doppler blood flow image denoising module implementing the method of any of claims 1-6, wherein: the color Doppler blood flow image noise reduction module is arranged between the blood flow processing unit and the scanning conversion unit and is used for further noise reduction processing on the speed signal image output by the blood flow processing unit;
the color Doppler blood flow image noise reduction module comprises: a moving window processing unit, a variance updating unit and a noise judging unit, wherein: the moving window processing unit circularly intercepts image blocks from the blood flow velocity signal diagram output by the blood flow processing unit and outputs the image blocks to the variance updating unit, the variance updating unit outputs the calculated diagonal displacement variance of the image blocks to the noise judging unit, and the noise judging unit feeds back the judgment result to the moving window processing unit and generates an updated blood flow velocity signal diagram.
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