CN108542422A - B ultrasound image optimization method, device and computer readable storage medium - Google Patents
B ultrasound image optimization method, device and computer readable storage medium Download PDFInfo
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5269—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving detection or reduction of artifacts
Abstract
The invention discloses a kind of B ultrasound image optimization method, device and computer readable storage medium, the method includes：By obtaining B ultrasound image to be optimized, logarithm inverse transformation is carried out to the B ultrasound image to be optimized, obtains echo-signal；Processing is optimized to the echo-signal；Linear transformation, the B ultrasound image after being optimized are carried out to the echo-signal after optimization.Since the echo-signal to B ultrasound image to be optimized optimizes, the influence of non-linear compression is evaded to a certain extent, optimization processing is directly handled the source signal of B ultrasound image to be optimized, it is stronger to optimize specific aim, the effect for improving B ultrasound image improves the contrast of image and the clarity of institutional framework.
Description
Technical field
It can the present invention relates to a kind of ultrasonic imaging technique field more particularly to B ultrasound image optimization method, device and computer
Read storage medium.
Background technology
Ultrasonic imaging because its is radiationless, it is cheap and clinical medicine application in be widely used.Because of Type B
The resolution ratio of ultrasonography is all related with ultrasonic frequency to imaging depth, in practical applications, for superficial organella and
Blood vessel imaging, the general linear array high-frequency ultrasonic probe using centre frequency 7.5MHz or more.Arteria carotis is human body superficial weight
The blood vessel wanted is the good window that atherosclerosis is observed, this is because atherosclerosis is one
Kind whole body Diffuse Diseases, and the observed result of arteria carotis has typicalness.For a B ultrasound imager, for arteria carotis
Imaging effect have become weigh its quality important indicator.In practical application, observation index has carotid intimal medial thickness,
Size, form and the characteristic of plaque, doctor judge the state of an illness of patient according to these indexs, and select corresponding treatment side
Case.
Current domestic low and middle-end B ultrasound imager also substantially standard configuration linear array high frequency probe, it is to meet clinical for shallow
The application demand of table high frequency imaging.But in the clinical diagnosis of carotid atherosclerosis, doctor needs in measuring in arteria carotis
The thickness of film, normal value only have 0.8mm-1.2mm, to the whole system performance including B ultrasound imager and linear high frequency probe
It is more demanding；In addition, the development of carotid atherosclerosis, can form patch, constituent is complicated, and different phase is different
The patch of type all respectively has feature, the ultrasonoscopy that B ultrasound imager is obtained that must not sympathize with these on ingredient and form
Condition, which has, well to be shown.The performance of domestic low and middle-end B ultrasound imager in these areas is all barely satisfactory, to carry out arteria carotis
In atherosis diagnosis, the image information referential provided reduces, and then influences the application of such equipment.
It can set about in terms of two for the optimization processing of B ultrasound carotid images, B ultrasound imaging on the one hand improved from system
Instrument improves its performance, is that the image obtained to system post-processes on the other hand, is retaining image content information as far as possible
Under the premise of, improve the effect that information shows.The former is related to system schema, hardware design, electronic device type selecting, analog- and digital- letter
It number processing and manufactures etc., input is big, the period is long, only system production producer is likely to accomplish.And system is obtained
The image taken post-processes, and less investment is quick.The post-processing optimization method for being currently based on image is typically all to use digitized map
The processing method of picture, processes for digital picture itself.
Invention content
The main purpose of the present invention is to provide a kind of B ultrasound image optimization method, device and computer readable storage medium,
Aim to solve the problem that the technical issues of can not being optimized in the prior art to B ultrasound image based on signal processing.
To achieve the above object, the present invention provides a kind of B ultrasound image optimization method, the described method comprises the following steps：
B ultrasound image to be optimized is obtained, logarithm inverse transformation is carried out to the B ultrasound image to be optimized, obtains echo-signal；
Processing is optimized to the echo-signal；
Linear transformation, the B ultrasound image after being optimized are carried out to the echo-signal after optimization.
Preferably, described that processing is optimized to the echo-signal, it specifically includes：
The dynamic range of the echo-signal is divided into several tissue compartments according to default mapping relations, described preset is reflected
The relationship of penetrating includes the correspondence of tissue and dynamic range；
Mean filter is carried out to the echo-signal of each tissue compartment；
Gaussian filtering is carried out to the echo-signal after progress mean filter；
Spot denoising is carried out to the echo-signal after progress gaussian filtering；
Enhancing processing is carried out to the echo-signal after progress spot denoising.
Preferably, the echo-signal to each tissue compartment carries out mean filter, specifically includes：
Mean filter is carried out to the echo-signal of each tissue compartment using default Filtering Model.
Preferably, the described pair of echo-signal progress gaussian filtering carried out after mean filter, specifically includes：
The row signal for obtaining the echo-signal after carrying out mean filter, calculates the filtering system of each signaling point in the row signal
Number；
The filter factor is normalized, and filter factor generates Gauss digital filtering according to treated
Device；
Gaussian filtering is carried out to the row signal of the echo-signal after being filtered according to the Gauss digital filter.
Preferably, the described pair of echo-signal progress spot denoising carried out after gaussian filtering, specifically includes：
The Selection Center signaling point in the echo-signal after carrying out gaussian filtering determines region of the center signal point
Block and search range；
The weighting coefficient of each signaling point within the scope of described search is determined according to the center signal point and the region sub-block；
The weighting coefficient of each signaling point within the scope of described search is normalized, and weighting is according to treated
Number generates non-local mean filter；
Spot denoising is carried out to the echo-signal after carrying out gaussian filtering according to the non-local mean filter.
Preferably, described that each signaling point within the scope of described search is determined according to the center signal point and the region sub-block
Weighting coefficient, specifically include：
The region sub-block for obtaining each signaling point within the scope of described search, calculates region sub-block and the institute of the center signal point
State the grey similarity of the region sub-block of each signaling point in search range；
Calculate the Gauss distance of the center signal point and each signaling point within the scope of described search；
Using the product of the gray scale similar value and the Gauss distance as the weighting of each signaling point within the scope of described search
Coefficient.
Preferably, the described pair of echo-signal carried out after spot denoising carries out enhancing processing, specifically includes：
Calculate carry out spot denoising after echo-signal Laplace operator, and according to the Laplace operator into
Echo-signal after row spot denoising is sharpened processing.
Preferably, the echo-signal after described pair of optimization carries out linear transformation, and the B ultrasound image after being optimized is specific to wrap
It includes：
Linear transformation is carried out to the dynamic range of the echo-signal after optimization；
Grey linear transformation, the B ultrasound image after being optimized are carried out to the echo-signal after progress linear transformation.
In addition, to achieve the above object, the present invention also provides a kind of B ultrasound image optimization device, the B ultrasound image optimization dress
Set including：Memory, processor and the B ultrasound image optimization journey that is stored on the memory and can run on the processor
The step of sequence, the B ultrasound image optimization program realizes the B ultrasound image optimization method when being executed by the processor.
In addition, to achieve the above object, it is described computer-readable the present invention also provides a kind of computer readable storage medium
B ultrasound image optimization program is stored on storage medium, the B ultrasound image optimization program realizes the B ultrasound when being executed by processor
The step of image optimization method.
In the present invention, by obtaining B ultrasound image to be optimized, logarithm inverse transformation is carried out to the B ultrasound image to be optimized, is obtained
Obtain echo-signal；Processing is optimized to the echo-signal；Linear transformation is carried out to the echo-signal after optimization, is optimized
B ultrasound image afterwards.Since the echo-signal to B ultrasound image to be optimized optimizes, non-linear pressure is evaded to a certain extent
The influence of contracting so that optimization processing can directly be handled the source signal of B ultrasound image to be optimized, and optimization specific aim is stronger,
The effect for improving B ultrasound image improves the contrast of image and the clarity of institutional framework.
Description of the drawings
Fig. 1 is the apparatus structure schematic diagram for the hardware running environment that the embodiment of the present invention is related to；
Fig. 2 is the flow diagram of B ultrasound image optimization method first embodiment of the present invention；
Fig. 3 is present invention B ultrasound image schematic diagram to be optimized；
Fig. 4 be the present invention optimization after after B ultrasound image schematic diagram；
Fig. 5 is the flow diagram of B ultrasound image optimization method second embodiment of the present invention；
Fig. 6 is the flow diagram of B ultrasound image optimization method 3rd embodiment of the present invention；
Fig. 7 is the flow diagram of B ultrasound image optimization method fourth embodiment of the present invention；
Fig. 8 is the mapping relations figure of grey linear transformation of the present invention.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific implementation mode
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
The solution of the embodiment of the present invention is mainly：By obtaining B ultrasound image to be optimized, to the B ultrasound figure to be optimized
As carrying out logarithm inverse transformation, echo-signal is obtained；Processing is optimized to the echo-signal；To the echo-signal after optimization into
Row linear transformation, the B ultrasound image after being optimized.Since the echo-signal to B ultrasound image to be optimized optimizes, in certain journey
Evaded the influence of non-linear compression on degree so that optimization processing can directly to the source signal of B ultrasound image to be optimized at
Reason, optimization specific aim is stronger, improves the effect of B ultrasound image, improves the contrast of image and the clarity of institutional framework.
Referring to Fig.1, Fig. 1 is the apparatus structure schematic diagram for the hardware running environment that the embodiment of the present invention is related to.
As shown in Figure 1, the B ultrasound image optimization device may include：Processor 1001, such as CPU, communication bus
1002, user interface 1003, network interface 1004, memory 1005.Wherein, communication bus 1002 for realizing these components it
Between connection communication.User interface 1003 may include display screen (Display), and optional user interface 1003 can also include mark
Wireline interface, the wireless interface of standard.Network interface 1004 may include optionally standard wireline interface and wireless interface (such as WI-
FI interfaces).Memory 1005 can be high-speed RAM memory, can also be stable memory (non-volatile
), such as magnetic disk storage memory.Memory 1005 optionally can also be the storage service independently of aforementioned processor 1001
Device.
The B ultrasound image optimization device can be physical equipment connected to the network.
It will be understood by those skilled in the art that structure shown in Fig. 1 is not constituted to the B ultrasound image optimization device
It limits, may include either combining certain components or different components arrangement than illustrating more or fewer components.
As shown in Figure 1, as may include operating system, net in a kind of memory 1005 of computer readable storage medium
Network communication module, Subscriber Interface Module SIM and B ultrasound image optimization program.
In the construction shown in fig. 1, network interface 1004 is mainly used for Connection Service device, and data are carried out with the server
Communication；User interface 1003 is mainly used for connecting B ultrasound imager, with B ultrasound imager into row data communication；The B ultrasound image is excellent
Makeup is set calls the B ultrasound image optimization program stored in memory 1005 by processor 1001, and executes following operation：
B ultrasound image to be optimized is obtained, logarithm inverse transformation is carried out to the B ultrasound image to be optimized, obtains echo-signal；
Processing is optimized to the echo-signal；
Linear transformation, the B ultrasound image after being optimized are carried out to the echo-signal after optimization.
Further, processor 1001 can call the B ultrasound image optimization program stored in memory 1005, also execute with
Lower operation：
The dynamic range of the echo-signal is divided into several tissue compartments according to default mapping relations, described preset is reflected
The relationship of penetrating includes the correspondence of tissue and dynamic range；
Mean filter is carried out to the echo-signal of each tissue compartment；
Gaussian filtering is carried out to the echo-signal after progress mean filter；
Spot denoising is carried out to the echo-signal after progress gaussian filtering；
Enhancing processing is carried out to the echo-signal after progress spot denoising.
Further, processor 1001 can call the B ultrasound image optimization program stored in memory 1005, also execute with
Lower operation：
Mean filter is carried out to the echo-signal of each tissue compartment using default Filtering Model.
Further, processor 1001 can call the B ultrasound image optimization program stored in memory 1005, also execute with
Lower operation：
The row signal for obtaining the echo-signal after carrying out mean filter, calculates the filtering system of each signaling point in the row signal
Number；
The filter factor is normalized, and filter factor generates Gauss digital filtering according to treated
Device；
Gaussian filtering is carried out to the row signal of the echo-signal after being filtered according to the Gauss digital filter.
Further, processor 1001 can call the B ultrasound image optimization program stored in memory 1005, also execute with
Lower operation：
The Selection Center signaling point in the echo-signal after carrying out gaussian filtering determines region of the center signal point
Block and search range；
The weighting coefficient of each signaling point within the scope of described search is determined according to the center signal point and the region sub-block；
The weighting coefficient of each signaling point within the scope of described search is normalized, and weighting is according to treated
Number generates non-local mean filter；
Spot denoising is carried out to the echo-signal after carrying out gaussian filtering according to the non-local mean filter.
Further, processor 1001 can call the B ultrasound image optimization program stored in memory 1005, also execute with
Lower operation：
The region sub-block for obtaining each signaling point within the scope of described search, calculates region sub-block and the institute of the center signal point
State the grey similarity of the region sub-block of each signaling point in search range；
Calculate the Gauss distance of the center signal point and each signaling point within the scope of described search；
Using the product of the gray scale similar value and the Gauss distance as the weighting of each signaling point within the scope of described search
Coefficient.
Further, processor 1001 can call the B ultrasound image optimization program stored in memory 1005, also execute with
Lower operation：
Calculate carry out spot denoising after echo-signal Laplace operator, and according to the Laplace operator into
Echo-signal after row spot denoising is sharpened processing.
Further, processor 1001 can call the B ultrasound image optimization program stored in memory 1005, also execute with
Lower operation：
Linear transformation is carried out to the dynamic range of the echo-signal after optimization；
Grey linear transformation, the B ultrasound image after being optimized are carried out to the echo-signal after progress linear transformation.
In the present embodiment, by obtaining B ultrasound image to be optimized, logarithm inverse transformation is carried out to the B ultrasound image to be optimized,
Obtain echo-signal；Processing is optimized to the echo-signal；Linear transformation is carried out to the echo-signal after optimization, is obtained excellent
B ultrasound image after change.Since the echo-signal to B ultrasound image to be optimized optimizes, evade to a certain extent non-linear
The influence of compression so that optimization processing can directly be handled the source signal of B ultrasound image to be optimized, and optimization specific aim is more
By force, the effect for improving B ultrasound image improves the contrast of image and the clarity of institutional framework.
Based on above-mentioned hardware configuration, the embodiment of B ultrasound image optimization method of the present invention is proposed.
It is the flow diagram of B ultrasound image optimization method first embodiment of the present invention with reference to Fig. 2, Fig. 2.
In the first embodiment, the B ultrasound image optimization method includes the following steps：
Step S10：B ultrasound image to be optimized is obtained, logarithm inverse transformation is carried out to the B ultrasound image to be optimized, obtains echo
Signal.
It is understood that in B ultrasound imager, ultrasonic sensor (also commonly referred to as popping one's head in) sends out ultrasonic wave entrance
Human body in communication process of the sound wave in tissue, has acoustic wave segment signal to return to probe, probe connects in each position
The ultrasonic signal received, referred to as echo-signal.The amplitude variation of echo-signal reflects the changes in microstructure in human body, with
The increase into depth in human body, acoustic signals can gradually decay, so before being converted to image and showing, system is according to depth
Degree can do the compensation of signal gain amplifier.Alleged echo-signal in the present invention is this signal after gain compensation.
It should be noted that being optimized to B ultrasound image based on signal processing to realize, first by B ultrasound figure to be optimized
As being converted into echo-signal.The B ultrasound image to be optimized refers to the B ultrasound generated using current domestic low and middle-end B ultrasound imager
Image, the image information referential provided is relatively low, have it is to be optimized, as shown in figure 3, Fig. 3 is present invention B ultrasound image to be optimized
Schematic diagram.
Since in ultrasonic system, the dynamic range for the echo-signal that B ultrasound imager actual acquisition obtains is much larger than general
Display can show the dynamic range of image, and there are the mismatches of dynamic range.Normally to show B ultrasound image, actually super
Generally using log-compressed in sound system, the range that the dynamic range compression of actual signal to general purpose display can be shown,
Achieve the purpose that improve weak signal contrast simultaneously, which is：B=D*Ln (s)+T, wherein parameter D and system
Gain is related, and parameter T reflections are the position of handled signal spacing on nonlinear transformation curve, the two parameter conducts
System input parameter, is adjusted according to different situations, and B is the gray value of image pixel.Therefore, by the B to be optimized
Hypergraph picture carries out logarithm inverse transformation, the B ultrasound image to be optimized can be converted to corresponding echo-signal, specifically, the logarithm
Model used in inverse transformation is s=exp (B-T)/D.
Step S20：Processing is optimized to the echo-signal.
It should be noted that the echo-signal is signal corresponding with the B ultrasound image to be optimized, by described
Echo-signal optimizes processing, can reach the effect optimized to the B ultrasound image to be optimized.
Step S30：Linear transformation, the B ultrasound image after being optimized are carried out to the echo-signal after optimization.
It is understood that after optimizing processing to echo-signal, by the echo-signal after optimization into line
Property conversion, the dynamic range of the echo-signal after optimization is re-compressed to the range that can be shown to display, after being optimized
B ultrasound image, as shown in figure 4, Fig. 4 be the present invention optimization after B ultrasound image schematic diagram.
In the concrete realization, the dynamic range for the signal that display can be shown is 0-255, will pass through linear transformation mould
Type：F (i)=255* (S (i)-Smin)/(Smax-Smin) linear transformation is carried out to the echo-signal, wherein F (i) is after converting
Signal, S (i) is former echo-signal, SminFor the minimum value of former echo-signal, SmaxFor the maximum value of former echo-signal, i is letter
Number sequential value, according to transformed echo signal form optimize after B ultrasound image.
In the present embodiment, by obtaining B ultrasound image to be optimized, logarithm inverse transformation is carried out to the B ultrasound image to be optimized,
Obtain echo-signal；Processing is optimized to the echo-signal；Linear transformation is carried out to the echo-signal after optimization, is obtained excellent
B ultrasound image after change.Since the echo-signal to B ultrasound image to be optimized optimizes, evade to a certain extent non-linear
The influence of compression so that optimization processing can directly be handled the source signal of B ultrasound image to be optimized, and optimization specific aim is more
By force, the effect for improving B ultrasound image improves the contrast of image and the clarity of institutional framework.
It is the flow diagram of B ultrasound image optimization method second embodiment of the present invention with reference to Fig. 5, Fig. 5, is based on above-mentioned Fig. 2
Shown in embodiment, propose the second embodiment of B ultrasound image optimization method of the present invention.
In a second embodiment, the step S20, specifically includes：
Step S201：The dynamic range of the echo-signal is divided into several tissue compartments according to default mapping relations,
The default mapping relations include the correspondence of tissue and dynamic range.
It should be noted that in order to carry out fine clinical detection to tissue position to be monitored, it will be according to human body
The physical characteristic of tissue and ultrasonic wave interaction, with clinical research acquisition as a result, classifying to tissue.Specifically
Assorting process includes：By tissue be divided into blood tissues, adipose tissue, musculature, fibr tissue, calcified tissue and its
It organizes six classes, wherein and blood tissues, adipose tissue, musculature, fibr tissue, calcified tissue belong to typical organization, according to
The dynamic range of each tissue is classified.
In the concrete realization, according to clinical research, if the dynamic range of signal is 0-255, dynamic range is the people of 0-4
Body tissue belongs to blood, and the tissue that dynamic range is 8-26 belongs to adipose tissue, and dynamic range is the tissue of 41-76
Belong to musculature, the tissue that dynamic range is 112-196 belongs to fibr tissue, and dynamic range is the human body of 221-255
Tissue belongs to calcified tissue, and the tissue that dynamic range is located at except above five histioid dynamic ranges belongs to other groups
It knits.In practical applications, according to the difference of B ultrasound imager model, the boundary value in these sections needs to finely tune, and the present embodiment is to this
It does not limit.According to the above sorting technique, the distribution of signal strength is divided into 9 sections, wherein other tissues have
4 sections of separation, by blood tissues, adipose tissue, musculature, fibr tissue, calcified tissue's five quasi-representative tissues isolation
It opens.
Step S202：Mean filter is carried out to the echo-signal of each tissue compartment.
It is understood that carrying out mean filter by the echo-signal to each tissue compartment, similar tissue can be reduced
Inter- object distance improves homogeneous groups and knits the consistency of signal strength in the picture so that the signal strength of similar tissue is closer to allusion quotation
Offset.
Step S203：Gaussian filtering is carried out to the echo-signal after progress mean filter.
It is to be appreciated that in B ultrasound arteria carotis imaging applications, the information of organizational hierarchy structure is very heavy on depth direction
It wants, these layering interfaces show as the row signal level distribution of echo-signal, draw in institutional framework classification and its processing procedure
The noise entered can destroy the flatness at these interfaces, can reach preferable effect using Gaussian filter.In the concrete realization,
Inbound signal is put to the echo-signal after carrying out mean filter using Gauss digital filter and carries out gaussian filtering.
Step S204：Spot denoising is carried out to the echo-signal after progress gaussian filtering.
It is understood that speckle noise is a kind of multiplicative noise, model is complicated, and the present embodiment is filtered by non-local mean
The speckle noise that wave device inhibits ultrasonography adjoint.
Step S205：Enhancing processing is carried out to the echo-signal after progress spot denoising.
It should be noted that B ultrasound imager obtain be one section of human body echo-signal, it is similar tissue have intensity
Consistency, different tissues intensity is different, and alleged enhancing refers to enhancing the boundary of different tissues echo-signal.Carrying out spot denoising
Afterwards, enhancing processing will be carried out to current echo-signal, to realize the edge strengthening between tissue.
In the present embodiment, the dynamic range of the echo-signal is divided into several tissue areas according to default mapping relations
Between, mean filter is carried out to the echo-signal of each tissue compartment, gaussian filtering is carried out to the echo-signal after progress mean filter,
Spot denoising is carried out to the echo-signal after progress gaussian filtering, the echo-signal after progress spot denoising is carried out at enhancing
Reason.By a series of optimization processings to echo-signal, a variety of noises in echo-signal are eliminated, have been reached to echo-signal
Effect of optimization so that the echo-signal after optimization can preferably fit optimization after B ultrasound image.
It is the flow diagram of B ultrasound image optimization method 3rd embodiment of the present invention with reference to Fig. 6, Fig. 6, is based on above-mentioned Fig. 5
Shown in embodiment, propose the 3rd embodiment of B ultrasound image optimization method of the present invention.
In the present embodiment, the step S202, specifically includes：
Mean filter is carried out to the echo-signal of each tissue compartment using default Filtering Model.
It is understood that the default Filtering Model is F=M+ λ * (S-M), wherein F is filtered signal value, S
For original signal value, M is the section representative value specified, and λ is coefficient, different according to the computational methods for obtaining lambda coefficient, the present embodiment
This is not limited, parameter inputs each section M and λ as an optimization, to adapt to different needs.
Further, the step S203, specifically includes：
Step S01：The row signal for obtaining the echo-signal after carrying out mean filter, calculates each signaling point in the row signal
Filter factor.
Step S02：The filter factor is normalized, and filter factor generates Gaussage according to treated
Word filter.
Step S03：The row signal of the echo-signal after being filtered is carried out according to the Gauss digital filter
Gaussian filtering.
It should be noted that in order to be smoothed to organizational interface, by by Gauss digital filter to current
Echo-signal is filtered.Calculate the filter factor of each signaling point in the row signal per a line；According to sum=∑ x (i), i=1,
The filter factor is normalized in 2,3 ..., n, g (i)=x (i)/sum, wherein and i is the sequential value of each signaling point,
X (i) is the filter factor of each signaling point, and sum is the sum of filter factor, and g (i) is the filter factor after gaussian filtering, according to height
This filtered filter factor generates Gauss digital filter；According to f (j)=∑ g (i) * S (j-k+i), i=1,2,3 ..., n
The row signal of every a line is filtered, wherein j is the location index of often row sampled value.
Further, the step S204, specifically includes：
Step S04：The Selection Center signaling point in the echo-signal after carrying out gaussian filtering determines the center signal point
Region sub-block and search range.
Step S05：Each signaling point within the scope of described search is determined according to the center signal point and the region sub-block
Weighting coefficient.
Step S06：The weighting coefficient of each signaling point within the scope of described search is normalized, and according to processing after
Weighting coefficient generate non-local mean filter.
Step S07：Spot is carried out according to the non-local mean filter to the echo-signal after carrying out gaussian filtering to go
It makes an uproar.
In the concrete realization, to carry out gaussian filtering after echo-signal carry out spot denoising, Selection Center signaling point, really
Fixed region sub-block and region of search centered on the center signal point, such as the region sub-block are with the center signal point
Centered on, size is the sub-block of 3*3, and described search region is centered on the center signal point, and size is the region of 5*5,
The present embodiment does not limit the value of region sub-block and search range, meets search range and is more than region sub-block.
After the region sub-block and the search range that determine center signal point, institute is calculated according to the center signal point and the region sub-block
Place is normalized to the weighting coefficient of each signaling point within the scope of described search in the weighting coefficient for stating each signaling point in search range
Reason, and weighting coefficient generates non-local mean filter according to treated, according to the non-local mean filter to carrying out
Echo-signal after gaussian filtering carries out spot denoising.
Further, the step S05, specifically includes：
The region sub-block for obtaining each signaling point within the scope of described search, calculates region sub-block and the institute of the center signal point
State the grey similarity of the region sub-block of each signaling point in search range.
Calculate the Gauss distance of the center signal point and each signaling point within the scope of described search.
Using the product of the gray scale similar value and the Gauss distance as the weighting of each signaling point within the scope of described search
Coefficient.
It is understood that for the other signals point in the search range, the region sub-block with center signal point is obtained
The region sub-block of same size calculates the grey similarity of other signals point and the region sub-block of center signal point, the gray scale
Similitude is measured with Euclidean distance.The Gauss distance for calculating other signals point and the center signal point simultaneously, by the same letter
Number corresponding grey similarity of point is multiplied with Gauss distance, takes weighting coefficient of the product as the signaling point.
Step S205, specifically includes：
Calculate carry out spot denoising after echo-signal Laplace operator, and according to the Laplace operator into
Echo-signal after row spot denoising is sharpened processing.
It should be noted that using the Laplace operator of the echo-signal after progress spot denoising to carrying out spot denoising
Echo-signal afterwards is sharpened processing, can protrude the boundary of different resistance value structures, and the edge between tissue is strengthened.Specifically
Calculation formula is：G (x, y)=f (x, y)+c [▽2F (x, y)], wherein g (x, y) is the signal after sharpening, and f (x, y) is to carry out
Echo-signal after spot denoising, c are sharpening coefficient, ▽2F (x, y) is Laplace operator.In field of digital signals, La Pu
Laplacian operater Available templates indicate that an Available templates of the present embodiment are：
| 0 | -1 | 0 |
| -1 | 4 | -1 |
| 0 | -1 | 0 |
In the present embodiment, the dynamic range of the echo-signal is divided into several tissue areas according to default mapping relations
Between, mean filter is carried out to the echo-signal of each tissue compartment, gaussian filtering is carried out to the echo-signal after progress mean filter,
Spot denoising is carried out to the echo-signal after progress gaussian filtering, the echo-signal after progress spot denoising is carried out at enhancing
Reason.By a series of optimization processings to echo-signal, a variety of noises in echo-signal are eliminated, have been reached to echo-signal
Effect of optimization so that the echo-signal after optimization can preferably fit optimization after B ultrasound image.
It is the flow diagram of B ultrasound image optimization method fourth embodiment of the present invention with reference to Fig. 7, Fig. 7, is based on above-mentioned Fig. 5
Shown in embodiment, propose the fourth embodiment of B ultrasound image optimization method of the present invention.
In the present embodiment, the step S30, specifically includes：
Step S301：Linear transformation is carried out to the dynamic range of the echo-signal after optimization.
It is understood that when B ultrasound image to be optimized is converted into echo-signal, dynamic range is increased, when right
After echo-signal optimizes processing, linear transformation will be carried out to the echo-signal after optimization so that the echo-signal after optimization
Dynamic range become range that as low as display can be shown.
In the concrete realization, the dynamic range for the signal that display can be shown is 0-255, will pass through linear transformation mould
Type：F (i)=255* (S (i)-Smin)/(Smax-Smin) linear transformation is carried out to the echo-signal, wherein F (i) is after converting
Signal, S (i) is former echo-signal, SminFor the minimum value of former echo-signal, SmaxFor the maximum value of former echo-signal, i is letter
Number sequential value, according to transformed echo signal form optimize after B ultrasound image.
Step S302：Grey linear transformation, the B ultrasound figure after being optimized are carried out to the echo-signal after progress linear transformation
Picture.
It should be noted that grey linear transformation is carried out to the echo-signal after carrying out linear transformation by preset formula,
The contrast enhancing of the echo-signal after linear transformation is allowed to carry out, the image effect of conversion is more preferably.Assuming that signal matrix
Width is w, is highly h, which is：
Wherein, i=1 ..., w, j=1 ..., h, f (i, j) be transformation before signal, g (i, j) be convert after signal, a,
B, c, fa, fb, ga and gb are constant, convert front and back signal contrast as shown in figure 8, Fig. 8 is grey linear transformation of the present invention
Mapping relations figure.
In the present embodiment, linear transformation is carried out by the dynamic range to the echo-signal after optimization, it is linear to carrying out
Echo-signal after transformation carries out grey linear transformation, the B ultrasound image after being optimized.Due to the echo-signal after optimization
Dynamic range carries out linear transformation so that the dynamic range of echo-signal is located at the model that can be performed image display by display
In enclosing, by carrying out grey linear transformation, the contrast of the B ultrasound image after optimization is improved so that effect of optimization is more preferably.
In addition, the embodiment of the present invention also proposes a kind of computer readable storage medium, the computer readable storage medium
On be stored with B ultrasound image optimization program, following operation is realized when the B ultrasound image optimization program is executed by processor：
B ultrasound image to be optimized is obtained, logarithm inverse transformation is carried out to the B ultrasound image to be optimized, obtains echo-signal；
Processing is optimized to the echo-signal；
Linear transformation, the B ultrasound image after being optimized are carried out to the echo-signal after optimization.
Further, following operation is also realized when the B ultrasound image optimization program is executed by processor：
The dynamic range of the echo-signal is divided into several tissue compartments according to default mapping relations, described preset is reflected
The relationship of penetrating includes the correspondence of tissue and dynamic range；
Mean filter is carried out to the echo-signal of each tissue compartment；
Gaussian filtering is carried out to the echo-signal after progress mean filter；
Spot denoising is carried out to the echo-signal after progress gaussian filtering；
Enhancing processing is carried out to the echo-signal after progress spot denoising.
Further, following operation is also realized when the B ultrasound image optimization program is executed by processor：
Mean filter is carried out to the echo-signal of each tissue compartment using default Filtering Model.
Further, following operation is also realized when the B ultrasound image optimization program is executed by processor：
The row signal for obtaining the echo-signal after carrying out mean filter, calculates the filtering system of each signaling point in the row signal
Number；
The filter factor is normalized, and filter factor generates Gauss digital filtering according to treated
Device；
Gaussian filtering is carried out to the row signal of the echo-signal after being filtered according to the Gauss digital filter.
Further, following operation is also realized when the B ultrasound image optimization program is executed by processor：
The Selection Center signaling point in the echo-signal after carrying out gaussian filtering determines region of the center signal point
Block and search range；
The weighting coefficient of each signaling point within the scope of described search is determined according to the center signal point and the region sub-block；
The weighting coefficient of each signaling point within the scope of described search is normalized, and weighting is according to treated
Number generates non-local mean filter；
Spot denoising is carried out to the echo-signal after carrying out gaussian filtering according to the non-local mean filter.
Further, following operation is also realized when the B ultrasound image optimization program is executed by processor：
The region sub-block for obtaining each signaling point within the scope of described search, calculates region sub-block and the institute of the center signal point
State the grey similarity of the region sub-block of each signaling point in search range；
Calculate the Gauss distance of the center signal point and each signaling point within the scope of described search；
Using the product of the gray scale similar value and the Gauss distance as the weighting of each signaling point within the scope of described search
Coefficient.
Further, following operation is also realized when the B ultrasound image optimization program is executed by processor：
Calculate carry out spot denoising after echo-signal Laplace operator, and according to the Laplace operator into
Echo-signal after row spot denoising is sharpened processing.
Further, following operation is also realized when the B ultrasound image optimization program is executed by processor：
Linear transformation is carried out to the dynamic range of the echo-signal after optimization；
Grey linear transformation, the B ultrasound image after being optimized are carried out to the echo-signal after progress linear transformation.
In the present embodiment, by obtaining B ultrasound image to be optimized, logarithm inverse transformation is carried out to the B ultrasound image to be optimized,
Obtain echo-signal；Processing is optimized to the echo-signal；Linear transformation is carried out to the echo-signal after optimization, is obtained excellent
B ultrasound image after change.Since the echo-signal to B ultrasound image to be optimized optimizes, evade to a certain extent non-linear
The influence of compression so that optimization processing can directly be handled the source signal of B ultrasound image to be optimized, and optimization specific aim is more
By force, the effect for improving B ultrasound image improves the contrast of image and the clarity of institutional framework.
It should be noted that herein, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that process, method, article or system including a series of elements include not only those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or system institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including this
There is also other identical elements in the process of element, method, article or system.
The embodiments of the present invention are for illustration only, can not represent the quality of embodiment.
The use of word first, second, and third does not indicate that any sequence, can these words be construed to title.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can add the mode of required general hardware platform to realize by software, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical scheme of the present invention substantially in other words does the prior art
Going out the part of contribution can be expressed in the form of software products, the computer software product be stored in one it is computer-readable
In storage medium (such as ROM/RAM, magnetic disc, CD), including some instructions use so that a station terminal equipment (can be mobile phone,
Computer, server, air conditioner or network equipment etc.) execute method described in each embodiment of the present invention.
It these are only the preferred embodiment of the present invention, be not intended to limit the scope of the invention, it is every to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of B ultrasound image optimization method, which is characterized in that the described method comprises the following steps：
B ultrasound image to be optimized is obtained, logarithm inverse transformation is carried out to the B ultrasound image to be optimized, obtains echo-signal；
Processing is optimized to the echo-signal；
Linear transformation, the B ultrasound image after being optimized are carried out to the echo-signal after optimization.
2. B ultrasound image optimization method as described in claim 1, which is characterized in that described to be optimized to the echo-signal
Processing, specifically includes：
The dynamic range of the echo-signal is divided into several tissue compartments according to default mapping relations, the default mapping is closed
System includes the correspondence of tissue and dynamic range；
Mean filter is carried out to the echo-signal of each tissue compartment；
Gaussian filtering is carried out to the echo-signal after progress mean filter；
Spot denoising is carried out to the echo-signal after progress gaussian filtering；
Enhancing processing is carried out to the echo-signal after progress spot denoising.
3. B ultrasound image optimization method as claimed in claim 2, which is characterized in that the echo-signal to each tissue compartment
Mean filter is carried out, is specifically included：
Mean filter is carried out to the echo-signal of each tissue compartment using default Filtering Model.
4. B ultrasound image optimization method as claimed in claim 3, which is characterized in that the described pair of echo carried out after mean filter
Signal carries out gaussian filtering, specifically includes：
The row signal for obtaining the echo-signal after carrying out mean filter, calculates the filter factor of each signaling point in the row signal；
The filter factor is normalized, and filter factor generates Gauss digital filter according to treated；
Gaussian filtering is carried out to the row signal of the echo-signal after being filtered according to the Gauss digital filter.
5. B ultrasound image optimization method as claimed in claim 4, which is characterized in that the described pair of echo carried out after gaussian filtering
Signal carries out spot denoising, specifically includes：
The Selection Center signaling point in the echo-signal after carrying out gaussian filtering, determine the center signal point region sub-block and
Search range；
The weighting coefficient of each signaling point within the scope of described search is determined according to the center signal point and the region sub-block；
The weighting coefficient of each signaling point within the scope of described search is normalized, and weighting coefficient is given birth to according to treated
At non-local mean filter；
Spot denoising is carried out to the echo-signal after carrying out gaussian filtering according to the non-local mean filter.
6. B ultrasound image optimization method as claimed in claim 5, which is characterized in that described according to the center signal point and institute
The weighting coefficient that region sub-block determines each signaling point within the scope of described search is stated, is specifically included：
The region sub-block of each signaling point within the scope of described search is obtained, the region sub-block for calculating the center signal point is searched with described
The grey similarity of the region sub-block of each signaling point within the scope of rope；
Calculate the Gauss distance of the center signal point and each signaling point within the scope of described search；
Using the product of the gray scale similar value and the Gauss distance as the weighting coefficient of each signaling point within the scope of described search.
7. B ultrasound image optimization method as claimed in claim 6, which is characterized in that the described pair of echo carried out after spot denoising
Signal carries out enhancing processing, specifically includes：
The Laplace operator of the echo-signal after carrying out spot denoising is calculated, and according to the Laplace operator to carrying out spot
Echo-signal after point denoising is sharpened processing.
8. the B ultrasound image optimization method as described in any one of claim 1-7, which is characterized in that returning after described pair of optimization
Wave signal carries out linear transformation, and the B ultrasound image after being optimized specifically includes：
Linear transformation is carried out to the dynamic range of the echo-signal after optimization；
Grey linear transformation, the B ultrasound image after being optimized are carried out to the echo-signal after progress linear transformation.
9. a kind of B ultrasound image optimization device, which is characterized in that the B ultrasound image optimization device includes：Memory, processor and
The B ultrasound image optimization program that is stored on the memory and can run on the processor, the B ultrasound image optimization program
It is realized such as the step of B ultrasound image optimization method described in any item of the claim 1 to 8 when being executed by the processor.
10. a kind of computer readable storage medium, which is characterized in that be stored with B ultrasound figure on the computer readable storage medium
As optimization program, such as B described in any item of the claim 1 to 8 is realized when the B ultrasound image optimization program is executed by processor
The step of super image optimization method.
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