CN110599405B - Ultrasonic image enhancement method and device and computer equipment - Google Patents
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Abstract
The application provides an ultrasonic image enhancement method, an ultrasonic image enhancement device and computer equipment. The ultrasonic image enhancement method provided by the application comprises the following steps: acquiring a coherence coefficient of each imaging point of an ultrasonic image to be processed; wherein the coherence coefficient of each imaging point is a coefficient for adjusting the gain of the beam forming data of the imaging point; determining the confidence coefficient of the pixel value of each imaging point according to the coherence coefficient of each imaging point of the ultrasonic image; wherein the confidence of the pixel value of each imaging point is positively correlated with the coherence coefficient of the imaging point; and carrying out enhancement processing on the ultrasonic image according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image. The ultrasonic image enhancement method, the ultrasonic image enhancement device and the computer equipment can obtain an enhanced image with higher contrast.
Description
Technical Field
The present disclosure relates to the field of image processing technologies, and in particular, to an ultrasound image enhancement method, an ultrasound image enhancement device, and a computer device.
Background
Ultrasound has the advantages of no harm to human body, real-time imaging, low cost and the like, and is widely applied to the medical detection field of organs such as blood vessels, bone density, heart and the like at present. Which forms an ultrasound image mainly by transmitting and receiving ultrasound waves to and from a subject. Currently, in order to improve the image quality of an ultrasound image, it is necessary to reduce unnecessary signal components included in a received signal, that is, side lobe components, grating lobe components, noise components, and the like.
At present, it has been found that phase aberration caused by non-uniformity of sound velocity is an important cause of degradation of ultrasound imaging quality. Therefore, it is important to reduce the degradation of the resolution and contrast of the ultrasound image due to the unevenness of the sound velocity and the side lobe component. In recent years, a method of reducing or suppressing unnecessary signal components contained in a received signal after the phasing and summing process has been proposed. The method employs the coherence coefficient to reject the received signal (e.g., multiplying the beamformed data by the coherence coefficient to obtain imaging data for imaging).
When the method is used for imaging, points with uneven sound velocity or points with strong side lobe components are forced to be pulled down, and the points with low original amplitude are confused, so that the contrast of an ultrasonic image is reduced. Currently, in order to improve the quality of an ultrasound image, an enhancement process is usually performed on the ultrasound image, and in the conventional method, the processing for each imaging point is the same, for example, the pixel value of each imaging point is multiplied by a corresponding enhancement coefficient, so as to obtain an enhanced image. Thus, when the ultrasound image formed by the above method is subjected to enhancement processing by the conventional method, the contrast of the enhanced image cannot be improved.
Disclosure of Invention
In view of this, the present application provides an ultrasound image enhancement method, apparatus and computer device, so as to process an ultrasound image to obtain an enhanced image with higher contrast.
A first aspect of the present application provides an ultrasound image enhancement method, including:
acquiring a coherence coefficient of each imaging point of an ultrasonic image to be processed; wherein the coherence coefficient of each imaging point is a coefficient for adjusting the gain of the beam forming data of the imaging point;
determining the confidence coefficient of the pixel value of each imaging point according to the coherence coefficient of each imaging point of the ultrasonic image; wherein the confidence of the pixel value of each imaging point is positively correlated with the coherence coefficient of the imaging point;
and carrying out enhancement processing on the ultrasonic image according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image.
A second aspect of the present application provides an ultrasound image enhancement device comprising: the device comprises an acquisition module, a determination module and a processing module, wherein the acquisition module is used for acquiring the coherence coefficient of each imaging point of an ultrasonic image to be processed; wherein the coherence coefficient of each imaging point is a coefficient for adjusting the gain of the beam forming data of the imaging point;
the determining module is used for determining the confidence coefficient of the pixel value of each imaging point according to the coherence coefficient of each imaging point of the ultrasonic image; wherein the confidence of the pixel value of each imaging point is positively correlated with the coherence coefficient of the imaging point;
the processing module is used for carrying out enhancement processing on the ultrasonic image according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image.
A third aspect of the present application provides a computer device comprising a memory, a processor and computer program instructions stored in the memory and executable by the processor, the program instructions, when executed by the processor, implementing the steps of any of the methods provided in the first aspect of the present application.
According to the ultrasonic image enhancement method, the ultrasonic image enhancement device and the computer equipment, the coherence coefficient of each imaging point of an ultrasonic image to be processed is obtained, and the confidence coefficient of the pixel value of each imaging point is determined according to the coherence coefficient of each imaging point of the ultrasonic image, so that the ultrasonic image is enhanced according to the confidence coefficient of the pixel value of each imaging point; wherein the confidence of the pixel value of each imaging point is positively correlated with the coherence coefficient of that imaging point. In this way, since the degree of the non-uniformity of the sound velocity and the degree of the strength of the side component have a positive correlation with the coherence coefficient, the confidence of the pixel value of each imaging point can be determined by the coherence coefficient, that is, the confidence of the pixel value of each imaging point is positively correlated with the coherence coefficient of the imaging point, and after the confidence of the pixel value of each imaging point is determined, when the ultrasound image is enhanced, the ultrasound image is enhanced according to the confidence of the pixel value of each imaging point. Thus, the contrast of the image can be improved after the ultrasonic image is processed.
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FIG. 1 is a flowchart of an embodiment of an ultrasound image enhancement method provided herein;
FIG. 2 is a schematic diagram of an implementation of an ultrasound image enhancement method according to an exemplary embodiment of the present application;
FIG. 3 is a flowchart of a second embodiment of an ultrasound image enhancement method provided herein;
FIG. 4 is a schematic diagram of an enhanced image obtained by fusing an ultrasound image and a filtered image according to an exemplary embodiment of the present application;
FIG. 5 is a hardware configuration diagram of a computer device in which an ultrasound image enhancement device according to an exemplary embodiment of the present application is located;
fig. 6 is a schematic structural diagram of an ultrasound image enhancement device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.
The terminology used in the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first message may also be referred to as a second message, and similarly, a second message may also be referred to as a first message, without departing from the scope of the present application. The word "if" as used herein may be interpreted as "at … …" or "at … …" or "responsive to a determination", depending on the context.
The application provides an ultrasonic image enhancement method, an ultrasonic image enhancement device and computer equipment, which are used for enhancing an ultrasonic image to obtain an enhanced image with higher contrast.
Fig. 1 is a flowchart of an embodiment of an ultrasound image enhancement method provided in the present application. Referring to fig. 1, the method provided in this embodiment may include:
s101, acquiring a coherence coefficient of each imaging point of an ultrasonic image to be processed; wherein the coherence coefficient of each imaging point is a coefficient for adjusting the gain of the beam forming data of the imaging point.
Specifically, the coherence coefficient of each imaging point is a coefficient for adjusting the gain of the beam forming data of the imaging point, and the coherence coefficient may be any one of the following coherence coefficients: CF. GCF, SCF, GSCF, STF. It should be noted that the ultrasound imaging system calculates the coherence coefficient of each imaging point during the beam forming stage. In this step, the coherence coefficient for each imaging point may be obtained from the ultrasound imaging system. The above-mentioned respective coherence coefficients are briefly described as follows:
specifically, the calculation formulas of various coherence coefficients are as follows:
si represents the amplitude of echo signals of different channels after delay calculation;
n represents the number of channels.
Specifically, when the amplitudes of the echo signals of different channels are the same, the power value of the direct current component of the echo signal is closer to the total power value of the frequency spectrum signal; the more the amplitude of the echo signals of different channels changes, the smaller the proportion of the power value of the direct current component of the echo signals to the total power value of the frequency spectrum signals.
Wherein bi represents sign bits of echo signals of different channels, bi= -1 when the amplitude of the echo signals is smaller than 0, bi=1 when the amplitude of the echo signals is larger than 0. The more the echo signal amplitudes of the different channels are the same, the closer the SCF is to 1.
GSCF represents the proportion of the total energy of the dc component in the symbol sequence of the echo signal, the more similar the GSCF is to 1 when the echo signal amplitudes of the different channels are the same.
Where bi represents the sign bit of the echo signal of the different channel, the more frequently the crossing with 0, the more c is 1, the closer a is to 0, and the smaller the stf.
S102, determining the confidence coefficient of the pixel value of each imaging point according to the coherence coefficient of each imaging point of the ultrasonic image; wherein the confidence of the pixel value of each imaging point is positively correlated with the coherence coefficient of that imaging point.
The pixel value of each imaging point refers to the data of the beam forming data after the coherence coefficient processing. Further, it is known from the principle of the coherence coefficient (for details, see description in the prior art, and not repeated here), the coherence coefficient can represent the degree of non-uniformity of the sound velocity and the degree of intensity of the side lobe component, and thus, the coherence coefficient can be used to represent the confidence of the pixel value of each imaging point.
Optionally, in a possible implementation manner of the present application, a specific implementation procedure of this step may include: the coherence coefficient for each imaging point is determined as a confidence in the pixel value for each imaging point.
S103, carrying out enhancement processing on the ultrasonic image according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image.
The greater the confidence of the pixel value of the imaging point, the less the imaging point is affected by the imaging point in its field during the enhancement process. The domain range may be specified by a user, and different domain ranges may be specified for different enhancement algorithms. In the present embodiment, this is not limited.
Specifically, through step S102, the confidence of the pixel value of each imaging point, that is, the reliability of the pixel value of the imaging point, may be calculated. In the step, when the ultrasonic image is enhanced, the ultrasonic image is processed by combining the confidence coefficient of each imaging point, when the confidence coefficient of the pixel value of the imaging point is larger, the pixel value of the imaging point is more reliable, and when the enhancement is performed, the imaging point is not easily affected by the imaging point in the field, and when the confidence coefficient of the pixel value of the imaging point is smaller, the pixel value of the imaging point is less reliable, and when the enhancement is performed, the imaging point is more easily affected by the imaging point in the field. In this way, the contrast of the image can be improved.
According to the method provided by the embodiment, the confidence coefficient of the pixel value of each imaging point is determined by acquiring the coherence coefficient of each imaging point of the ultrasonic image to be processed, so that the ultrasonic image is enhanced according to the confidence coefficient of the pixel value of each imaging point; wherein the confidence of the pixel value of each imaging point is positively correlated with the coherence coefficient of that imaging point. In this way, since the degree of the non-uniformity of the sound velocity and the procedure of the strength of the side lobe component have a positive correlation with the coherence coefficient, the confidence of the pixel value of each imaging point can be determined by the coherence coefficient, that is, the confidence of the pixel value of each imaging point is positively correlated with the coherence coefficient of the imaging point, and after the confidence of the pixel value of each imaging point is determined, when the ultrasound image is enhanced, the ultrasound image is enhanced according to the confidence of the pixel value of each imaging point. In this way, the contrast of the image can be improved.
Optionally, in a possible implementation manner of the present application, step S103 specifically includes:
according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image, adopting a bilateral filtering algorithm to enhance the ultrasonic image; the gray domain weight corresponding to each imaging point in the bilateral filtering algorithm is calculated by adopting a first formula or a second formula;
the first formula is:
the second formula is:
wherein ,
the gray domain weight corresponding to the imaging point p;
σ r is the gray standard deviation based on a Gaussian function;
I p pixel values for imaging point p;
I q pixel value of field imaging point q which is imaging point p;
wp is the confidence of the pixel value of the imaging point p.
Specifically, in this embodiment, a bilateral filtering algorithm is used to process the ultrasound image, where, unlike the prior art, in this embodiment, the gray domain weight corresponding to each imaging point in the bilateral filtering algorithm is calculated by using a first formula or a second formula. In this way, the contrast of the image can be improved.
It should be noted that, the definition of the bilateral filtering algorithm is as follows:
wherein ,
a gray domain weight corresponding to each imaging point;
wp is a standard quantity;
s is the domain range.
It should be noted that, for the specific calculation process and calculation principle of the spatial domain weight of each imaging point, reference may be made to the description in the prior art, and no further description is given here.
Alternatively, in another possible implementation manner of the present application, the specific implementation procedure of step S103 may include:
according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image, adopting an anisotropic diffusion model to enhance the ultrasonic image; wherein, the characteristic value of the diffusion tensor in the anisotropic diffusion model is calculated by adopting a third formula, and the third formula is as follows:
λ 2 ＝a
wherein ,λ1 、λ 2 Is a eigenvalue of the diffusion tensor; lambda (lambda) 1 A feature vector corresponding to the parallel gradient direction; lambda (lambda) 2 A feature vector corresponding to a direction perpendicular to the gradient;
a. s are constants;
w p a coherence coefficient for an imaging point p in the ultrasound image;
μ 1 、μ 2 is a feature value of the structure tensor; mu (mu) 1 Corresponding to parallel gradient directionIs a feature vector of (1); mu (mu) 2 Corresponding to a feature vector perpendicular to the gradient direction.
Specifically, in the method provided in this embodiment, the anisotropic diffusion model is used to process the ultrasound image, unlike the prior art, the calculation formula of the eigenvalue of the diffusion tensor in the anisotropic diffusion model is different, and in this embodiment, the third formula is used to calculate the eigenvalue of the diffusion tensor. In this way, the contrast of the image can be improved.
Fig. 2 is a schematic diagram illustrating an implementation of an ultrasound image enhancement method according to an exemplary embodiment of the present application. Referring to fig. 2, the ultrasound image enhancement method provided in the present application applies the correlation coefficient to the image enhancement process. In this way, the contrast of the image can be improved.
A more specific embodiment is given below for describing in detail the technical solution of the present application. Fig. 3 is a flowchart of a second embodiment of an ultrasound image enhancement method provided in the present application, referring to fig. 3, the method provided in the present embodiment, step S103 may include:
301. and obtaining beam synthesis data of each imaging point according to the pixel value of each imaging point of the ultrasonic image and the coherence coefficient of each imaging point.
Specifically, referring to the foregoing description, the pixel value of each imaging point of the ultrasound image is a value obtained by subjecting the beamformed data of each imaging point to a coherence coefficient, for example, a value obtained by multiplying the beamformed data of each imaging point by the coherence coefficient. According to the pixel value of each imaging point of the ultrasonic image and the coherence coefficient of each imaging point, the inverse operation corresponding to the coherence coefficient processing can be carried out on the pixel value of each imaging point, so as to obtain the beam synthesis data of each imaging point. For example, when the coherence coefficient is processed to multiply the beamformed data of each imaging point by the value of the coherence coefficient, at this time, the pixel value of each imaging point is divided by the coherence coefficient of the imaging point to obtain the beamformed data of the imaging point.
S302, obtaining a beam synthesis image according to the beam synthesis data of each imaging point.
S303, filtering the beam synthesis image to obtain a filtering image.
Specifically, the existing filtering algorithm may be used to perform filtering processing on the beam-formed image, which is not limited in this embodiment. For example, in one embodiment, the beamformed image may be subjected to 8-domain filtering to obtain a filtered image.
S304, fusion processing is carried out on the ultrasonic image and the filtering processing image according to the coherence coefficient of each imaging point of the ultrasonic image, so as to obtain an enhanced image.
Specifically, the specific implementation process of this step may include:
according to a fourth formula, carrying out fusion processing on the ultrasonic image and the filtering processing image to obtain an enhanced image; the fourth formula is:
R(i)＝wi*A(i)+(1-wi)B(i)
wherein R (i) is the pixel value of an imaging point i in the enhanced image;
wi is the coherence coefficient of an imaging point i in the ultrasound image;
a (i) is the pixel value of an imaging point i in the ultrasonic image;
b (i) is the pixel value of the imaging point i in the filter processed image.
Specifically, fig. 4 is a schematic diagram of an enhanced image obtained by performing fusion processing on an ultrasound image and a filter processing image according to an exemplary embodiment of the present application. Referring to fig. 4, fig. 4 is a diagram a of an ultrasound image, fig. 4 is a filtered image, fig. C is an enhanced image obtained by fusing the ultrasound image and the filtered image, and comparing the diagram a and the diagram C of fig. 4, it can be seen that black-spot noise introduced by the coherence coefficient processing can be reduced and the contrast of the image can be improved after the ultrasound image is processed by the method.
Corresponding to the embodiments of the ultrasound image enhancement method described above, embodiments of the ultrasound image enhancement device are also provided.
Embodiments of the ultrasound image enhancement apparatus of the present application may be applied to a computer device. The apparatus embodiments may be implemented by software, or may be implemented by hardware or a combination of hardware and software. Taking software implementation as an example, the device in a logic sense is formed by reading corresponding computer program instructions in a nonvolatile memory into a memory by a processor of a computer device where the device is located for operation. In terms of hardware, as shown in fig. 5, a hardware structure diagram of a computer device where an ultrasound image enhancement device is shown in an exemplary embodiment of the present application is shown, and in addition to the memory 510, the processor 520, the memory 530 and the network interface 540 shown in fig. 5, the computer device where the device is shown in the embodiment generally includes other hardware according to the actual function of the ultrasound image enhancement device, which is not described herein again.
Fig. 6 is a schematic diagram of an embodiment of an ultrasound image enhancement method provided in the present application. Referring to fig. 6, the apparatus provided in this embodiment may include: an acquisition module 610, a determination module 620, and a processing module 630, wherein,
the acquiring module 610 is configured to acquire a coherence coefficient of each imaging point of the ultrasound image to be processed; wherein the coherence coefficient of each imaging point is a coefficient for adjusting the gain of the beam forming data of the imaging point;
the determining module 620 is configured to determine a confidence level of a pixel value of each imaging point according to a coherence coefficient of each imaging point of the ultrasound image; wherein the confidence of the pixel value of each imaging point is positively correlated with the coherence coefficient of the imaging point;
the processing module 630 is configured to perform enhancement processing on the ultrasound image according to the confidence level of the pixel value of each imaging point of the ultrasound image.
The device of the present embodiment may be used to implement the technical solution of the method embodiment shown in fig. 1, and its implementation principle and technical effects are similar, and are not described here again.
Further, the determining module 620 is specifically configured to determine the coherence coefficient of each imaging point as a confidence level of the pixel value of each imaging point.
Further, the processing module 630 is specifically configured to:
according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image, adopting a bilateral filtering algorithm to enhance the ultrasonic image; the gray domain weight corresponding to each imaging point in the bilateral filtering algorithm is calculated by adopting a first formula or a second formula;
the first formula is:
the second formula is:
wherein ,
the gray domain weight corresponding to the imaging point p;
σ r is the gray standard deviation based on a Gaussian function;
I p pixel values for imaging point p;
I q pixel value of field imaging point q which is imaging point p;
wp is the confidence of the pixel value of the imaging point p.
Further, the processing module 630 is specifically configured to:
according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image, adopting an anisotropic diffusion model to enhance the ultrasonic image; the characteristic value of the diffusion tensor in the anisotropic diffusion model is calculated by adopting a third formula, wherein the third formula is as follows:
λ 2 ＝a
wherein ,λ1 、λ 2 Is a eigenvalue of the diffusion tensor; lambda (lambda) 1 Corresponding toFeature vectors parallel to the gradient direction; lambda (lambda) 2 A feature vector corresponding to a direction perpendicular to the gradient;
a. s are constants;
w p a coherence coefficient for an imaging point p in the ultrasound image;
μ 1 、μ 2 is a feature value of the structure tensor; mu (mu) 1 A feature vector corresponding to the parallel gradient direction; mu (mu) 2 Corresponding to a feature vector perpendicular to the gradient direction.
Further, the processing module 630 is specifically configured to:
obtaining beam synthesis data of each imaging point according to the pixel value of each imaging point of the ultrasonic image and the coherence coefficient of each imaging point;
according to the beam synthesis data of each imaging point, obtaining a beam synthesis image;
performing filtering processing on the beam synthesis image to obtain a filtering processing image;
and carrying out fusion processing on the ultrasonic image and the filtering processing image according to the coherence coefficient of each imaging point of the ultrasonic image to obtain an enhanced image.
Further, the fusing processing is performed on the ultrasound image and the filtering processing image according to the coherence coefficient of each imaging point of the ultrasound image, so as to obtain an enhanced image, which includes:
performing fusion processing on the ultrasonic image and the filtering processing image according to a fourth formula to obtain an enhanced image; the fourth formula is:
R(i)＝wi*A(i)+(1-wi)B(i)
wherein R (i) is the pixel value of an imaging point i in the enhanced image;
wi is the coherence coefficient of an imaging point i in the ultrasound image;
a (i) is the pixel value of an imaging point i in the ultrasonic image;
b (i) is the pixel value of the imaging point i in the filter processed image.
With continued reference to fig. 5, the present application further provides a computer device, including a memory, a processor, and computer program instructions stored in the memory and executable by the processor, where the program instructions, when executed by the processor, implement the steps of any of the ultrasound image enhancement methods provided herein.
The foregoing description of the preferred embodiments of the present invention is not intended to limit the invention to the precise form disclosed, and any modifications, equivalents, improvements and alternatives falling within the spirit and principles of the present invention are intended to be included within the scope of the present invention.
Claims (9)
1. A method of ultrasound image enhancement, the method comprising:
acquiring a coherence coefficient of each imaging point of an ultrasonic image to be processed; wherein the coherence coefficient of each imaging point is a coefficient for adjusting the gain of the beam forming data of the imaging point;
determining the confidence coefficient of the pixel value of each imaging point according to the coherence coefficient of each imaging point of the ultrasonic image; wherein the confidence of the pixel value of each imaging point is positively correlated with the coherence coefficient of the imaging point;
and carrying out enhancement processing on the ultrasonic image according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image, wherein the enhancement processing comprises the following steps: obtaining beam synthesis data of each imaging point according to the pixel value of each imaging point of the ultrasonic image and the coherence coefficient of each imaging point;
according to the beam synthesis data of each imaging point, obtaining a beam synthesis image;
performing filtering processing on the beam synthesis image to obtain a filtering processing image;
and carrying out fusion processing on the ultrasonic image and the filtering processing image according to the coherence coefficient of each imaging point of the ultrasonic image to obtain an enhanced image.
2. The method of claim 1, wherein determining the confidence level of the pixel value of each imaging point based on the coherence coefficient of each imaging point of the ultrasound image comprises:
the coherence coefficient for each imaging point is determined as a confidence in the pixel value for each imaging point.
3. The method of claim 1, wherein the enhancing the ultrasound image in accordance with the confidence level of the pixel value of each imaging point of the ultrasound image comprises:
according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image, adopting a bilateral filtering algorithm to enhance the ultrasonic image; the gray domain weight corresponding to each imaging point in the bilateral filtering algorithm is calculated by adopting a first formula or a second formula;
the first formula is:
the second formula is:
wherein ,
the gray domain weight corresponding to the imaging point p;
4. The method of claim 1, wherein the enhancing the ultrasound image in accordance with the confidence level of the pixel value of each imaging point of the ultrasound image comprises:
according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image, adopting an anisotropic diffusion model to enhance the ultrasonic image; the characteristic value of the diffusion tensor in the anisotropic diffusion model is calculated by adopting a third formula, wherein the third formula is as follows:
wherein ,
is a eigenvalue of the diffusion tensor; />
A feature vector corresponding to the parallel gradient direction;
5. the method of claim 1, wherein the fusing the ultrasound image and the filter processed image according to the coherence coefficient of each imaging point of the ultrasound image to obtain an enhanced image comprises:
performing fusion processing on the ultrasonic image and the filtering processing image according to a fourth formula to obtain an enhanced image; the fourth formula is:
R(i)=wi*A(i)+(1- wi)B(i)
wherein R (i) is the pixel value of an imaging point i in the enhanced image;
wi is the coherence coefficient of an imaging point i in the ultrasound image;
a (i) is the pixel value of an imaging point i in the ultrasonic image;
b (i) is the pixel value of the imaging point i in the filter processed image.
6. An ultrasound image enhancement device, the device comprising: the device comprises an acquisition module, a determination module and a processing module, wherein,
the acquisition module is used for acquiring the coherence coefficient of each imaging point of the ultrasonic image to be processed; wherein the coherence coefficient of each imaging point is a coefficient for adjusting the gain of the beam forming data of the imaging point;
the determining module is used for determining the confidence coefficient of the pixel value of each imaging point according to the coherence coefficient of each imaging point of the ultrasonic image; wherein the confidence of the pixel value of each imaging point is positively correlated with the coherence coefficient of the imaging point;
the processing module is used for obtaining beam synthesis data of each imaging point according to the pixel value of each imaging point of the ultrasonic image and the coherence coefficient of each imaging point;
according to the beam synthesis data of each imaging point, obtaining a beam synthesis image;
performing filtering processing on the beam synthesis image to obtain a filtering processing image;
and carrying out fusion processing on the ultrasonic image and the filtering processing image according to the coherence coefficient of each imaging point of the ultrasonic image to obtain an enhanced image.
7. The apparatus according to claim 6, wherein the determining module is configured to determine the coherence coefficient of each imaging point as a confidence level of the pixel value of each imaging point.
8. The apparatus of claim 6, wherein the processing module is specifically configured to:
according to the confidence coefficient of the pixel value of each imaging point of the ultrasonic image, adopting a bilateral filtering algorithm to enhance the ultrasonic image; the gray domain weight corresponding to each imaging point in the bilateral filtering algorithm is calculated by adopting a first formula or a second formula;
the first formula is:
the second formula is:
wherein ,
the gray domain weight corresponding to the imaging point p;
9. A computer device comprising a memory, a processor and computer program instructions stored in the memory and executable by the processor, the program instructions, when executed by the processor, carrying out the steps of the method of any one of claims 1-5 of the present application.
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| CN1214901A (en) * | 1997-09-22 | 1999-04-28 | 通用电气公司 | Ultrasonic image coherent filtering method and device |
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| CN104902824A (en) * | 2013-01-09 | 2015-09-09 | 日立阿洛卡医疗株式会社 | Ultrasonic diagnostic device |
| CN106600550A (en) * | 2016-11-29 | 2017-04-26 | 深圳开立生物医疗科技股份有限公司 | Ultrasonic image processing method and system |
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| CN1214901A (en) * | 1997-09-22 | 1999-04-28 | 通用电气公司 | Ultrasonic image coherent filtering method and device |
| CN104902824A (en) * | 2013-01-09 | 2015-09-09 | 日立阿洛卡医疗株式会社 | Ultrasonic diagnostic device |
| CN103536316A (en) * | 2013-09-22 | 2014-01-29 | 华中科技大学 | Method for self-adaptation ultrasonic imaging of spatio-temporally smoothed coherence factor type |
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