CN109330669A - A kind of ultrasound guided puncture image processing system and method based on virtual reality - Google Patents
A kind of ultrasound guided puncture image processing system and method based on virtual reality Download PDFInfo
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Classifications
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B17/00—Surgical instruments, devices or methods, e.g. tourniquets
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- A61B17/3403—Needle locating or guiding means
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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- A61B17/34—Trocars; Puncturing needles
- A61B17/3403—Needle locating or guiding means
- A61B2017/3413—Needle locating or guiding means guided by ultrasound
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- G06T2207/20048—Transform domain processing
Abstract
The invention belongs to field of medical technology, a kind of ultrasound guided puncture image processing system and method based on virtual reality is disclosed, image processing system includes: image capture module, image enhancement module, central control module, image conversion module, track navigation module, piercing module, virtual display module.The present invention can obtain the more crucial image stream comprising needle body according to the image stream that the launch angle sequence generates by image enhancement module, after carrying out denoising, fusion to the image stream comprising needle body, obtain the enhancing image of ultrasonic puncture needle, and the enhancing image of ultrasonic puncture needle is apparent, accurate, the ultrasound image for subsequent accurate analysis user itself provides strong foundation；Virtual reality technology is applied in ultrasonic puncture operation by image conversion module, virtual display module simultaneously, enhances the three-dimensional sense and flexibility of display, helps the faster and better completion operation of doctor.
Description
Technical field
The invention belongs to field of medical technology more particularly to a kind of ultrasound guided puncture image procossings based on virtual reality
System and method.
Background technique
Currently, the prior art commonly used in the trade is such that
Puncture is a medical surgery term, be will puncture be needled into body cavity extract secretion chemically examine, to body cavity inject
Gas or contrast agent do contrast examination, or into body cavity injection of medicine a kind of Clinics.The purpose of puncture is blood test,
Blood transfusion, infusion and merging conduit do angiography.Puncture includes: bone marrow puncture, has crista iliaca to puncture, spinal crest of Rauber punctures and chest
Bone punctures.Diagnosis for blood disease, certain parasitic diseases such as kala-azar.There is hemorrhagic tendency person to forbid doing bone marrow aspiration.Lymph
Centesis is tied, for puncturing the unknown superficial lymph knot of reason, Extract can do chemical examination and pathologic finding.But malignant lymphatic tumor
Examination by centesis is not answered in lymph node with depth.Arthrocentesis, have shoulder joint chamber, elbow joint chamber, wrist joint chamber, hip joint,
Knee joint cavity and ankle-joint chamber puncture.After puncture can drawing liquid chemical examination, can also inject air study and injection of medicine treatment.Articular cavity
Puncture requires rigorous aseptic, prevents infection.Arthropathy, the articular cavity tumour unknown suitable for reason etc..Vessel puncture, it is common
Such as femoral artery puncture, femoral venous puncture and subclavian vein puncture.Purpose be blood test, blood transfusion, infusion (including merging lead
Pipe retain infusion) and merging conduit do angiography.Blood vessel can puncture blood drawing at three.Subclavian vein is placed in after can puncturing
Conduit retains, and does intravenous hyperalimentation treatment.The heart, cerebral angiography can be done by puncturing femoral artery merging conduit.However, existing puncture
Image Acquisition poor definition, data inaccuracy in operation；Existing lancing system shows that display effect is poor by plane simultaneously, no
Conducive to doctor's stereovision.
In conclusion problem of the existing technology is:
Image Acquisition poor definition, data inaccuracy in existing puncturing operation.
Existing lancing system shows that display effect is poor by plane simultaneously, is unfavorable for doctor's stereovision.
There is halation, loss in detail in image in existing puncturing operation.
Existing operation plan discussion can not accurately analog subscriber situation.
For the layering analysis method of three-dimensional scenic cognitive network resource, in the prior art, not using characteristic parameter as
Latitude coordinates construct the multidimensional vector space of resource element, construct complete cognitive network resource by latitude coordinates of resource element
Multidimensional vector space.In such two-stage vector space model, it cannot make each vector that there is specific physical resource to contain
Justice.
Summary of the invention
In view of the problems of the existing technology, the present invention provides a kind of ultrasound guided puncture image based on virtual reality
Processing system and method.
The invention is realized in this way a kind of ultrasound guided puncture image processing method based on virtual reality, the base
Include: in the ultrasound guided puncture image processing method of virtual reality
Acquisition user waits for site of puncture image data；Enhancing processing operation is carried out to the image of acquisition；
Three-dimensional scenic is converted by three-dimensional software production by the image of acquisition；It include: to be provided in three-dimensional scenic cognition network
The resource space model that source element is constituted
In, wherein Y indicates that 2D-FWHT becomes
The matrix of consequence changed, H4Indicate the coefficient matrix of 2D-FWHT transformation,Indicate H4Transposed matrix, X indicate candidate blocks data
The matrix of composition；
The resource that one-dimensional fast Hadamard transform indicates that cognition network system senses obtain is carried out with the form of state vector
State, one-dimensional fast Hadamard transform are as follows:
Wherein, Y indicates the matrix of consequence of 1D-FWHT transformation, H8Indicate that the coefficient matrix of 1D-FWHT transformation, X indicate candidate
Block number according to composition matrix；
And the hypersurface in multi dimensional resource space is constituted using the set that all resource status vectors are formed；And multidimensional is provided
Hypersurface in source space carries out threshold decision output；
Wherein, Y indicates hard -threshold processing result, and X indicates three-dimensional Hadamard transform as a result, Threshold expression judges threshold
Value, sigma indicate noise estimate variance；
One-dimensional inverse fast Hadamard transform, 2 dimension inverse fast Hadamard transforms are carried out after threshold decision output, obtain block estimation
As a result；
One-dimensional inverse fast Hadamard transform includes:
Wherein, Y indicates the matrix of consequence of 1D-IFWHT transformation, H8Indicate that the coefficient matrix of 1D-IFWHT transformation, X indicate hard
Threshold process result forms column vector；
2, which tie up inverse fast Hadamard transforms, includes:
Wherein, Y indicates the matrix of consequence of 2D-IFWHT transformation, H4Indicate the coefficient matrix of 2D-IFWHT transformation,It indicates
H4Transposed matrix, X indicates the matrix of one-dimensional inverse transformed result composition；
The constraint condition for judging resource status availability is formed according to the demand of communication service, and is sentenced with the constraint condition
Whether each state vector on disconnected resource status hypersurface meets the constraint condition, will select the qualified state come
Set of vectors constitutes available resources state hypersurface；
By the available resources state hypersurface of formation at all resource vectors for meeting constraint condition in resource space
Regional scope forms available resources space；
Resource allocation algorithm is set, and selects state optimal in the available resources space with the resource allocation algorithm
Vector；Obtain accurate three-dimensional scene images data.
Further, the ultrasound guided puncture image processing method based on virtual reality further comprises:
Determine the track navigation punctured；User's operation station diagram picture is confirmed.
It determines in the track navigation punctured, track navigation optimizing is carried out using the method for optimal path, is specifically included:
1) bat individual is encoded based on the probability amplitude on the basis of basic bat algorithm using quantum bit, i.e. dosage
Sub- revolving door is updated the probability amplitude of quantum bit, is received using quantum non-gate as mutation operation to avoid the precocity of algorithm
It holds back；For each quantum bit tool, there are two probability amplitudes, and therefore, every bat can indicate two positions in optimization space；
2) in quantum calculation, the smallest information unit is stored in a quantum bit, and the state of the quantum bit can
Can be " 0 ", it is also possible to the free position between " 1 ", or " 0 " and " 1 "；The state of one quantum bit is expressed as follows:
| Ψ >=α | 0 >+β | 1 >
Wherein, α and β meets:
| α | 2+ | β | 2=1
Wherein, | α | 2 Hes | β | 2 respectively indicate and tend to state | 0 > and | 1 > probability；
One n member quantum bit are as follows:
Quantum rotating gate is as follows:
Quantum non-gate is as follows:
3) generate initial population: the encoding scheme of use is as follows:
Wherein, θ ij is argument, by formula (17) it can be seen that every bat has corresponded to two positions of problem space, respectively
Corresponded to quantum state | 0 > and | 1 > probability amplitude:
Pic=(cos (θ i1), cos (θ i2) ..., cos (θ in))
Pis=(sin (θ i1), sin (θ i2) ..., sin (θ in))
4) conversion of solution space:
To calculate the fitness of individual and evaluating the superiority and inferiority of individual, need to convert the solution space of population；
Each probability amplitude of the quantum bit of individual has corresponded to a solution of the solution space of problem, i.e., every bat has corresponded to optimization problem
Two solutions；
Wherein,By quantum state | 0 > probability amplitudeIt acquires, andBy quantum state | 1 > probability amplitude
It obtains；
5) more new strategy:
In quantum bat algorithm (QBA), using bat algorithm (BA) more new strategy to the argument increment of quantum bit into
Row updates, and renewal process is as follows:
Δ θ ij (t+1)=Δ θ ij (t)+Δ θ g*Q (i) * stepnow
θ ij (t+1)=θ ij (t)+Δ θ ij (t+1)
Wherein, Δ θ ij and θ ij are respectively argument increment and argument；
Parameter value in formula is respectively as follows: w=2, σ e=0, σ s=2；
Probability amplitude is updated using Quantum rotating gate:
Obtain two new positions:
6) Mutation Strategy:
In quantum bat algorithm (QBA), algorithm prematurely falls into local optimum in order to prevent, uses Mutation Strategy herein
Increase the diversity of population, Mutation Strategy passes through quantum non-gate and realize；If rand () < pm, quantum non-gate behaviour is executed
Make, two probability values are exchanged；Wherein, pm is mutation probability；
Further, the ultrasound guided puncture image processing method based on virtual reality further comprises:
Show the virtual scene of site of puncture.
Further, image method includes:
Firstly, emitting deflection angle according to preset ultrasonic wave generates launch angle sequence, the preset ultrasonic wave transmitting
Deflection angle is arranged according to the frequency attribute and imaging characteristics of probe；
Secondly, generating the image stream of different attribute feature according to the launch angle sequence；
Then, described image stream is performed corresponding processing respectively according to the different attribute feature of image stream；
Finally, the image stream after fusion treatment, to obtain the enhancing image of ultrasonic puncture needle；
Emit deflection angle generation launch angle sequence according to preset ultrasonic wave to specifically include:
Predetermined angle difference threshold value；
Emit deflection angle and preset differential seat angle threshold value according to preset ultrasonic wave, generate launch angle sequence, generates
The differential seat angle of two neighboring launch angle be less than preset differential seat angle threshold value, preset ultrasonic wave transmitting deflection angle is adjacent thereto
Generation launch angle differential seat angle be less than preset differential seat angle threshold value.
Further, acquisition user waits in site of puncture image data that image scene is by the reality with certain physics consistency
Body composition, the picture signal λ that entity issues1It indicates are as follows:
λ1=λ '+λr
Wherein, λ ' is radial component, λrFor reflecting component, since other subject matters also have light reflection in scene, on
Formula expands are as follows:
λ 1=λ '+λrs+λ0
λrsIt is degeneration factor, λ0For target reflecting component in scene, site of puncture image capturing system is waited for for user and
Speech, which is main component, and λrsIt is relatively small；From imaging is extracted degradation effect occurs for signal, and the degree of degeneration depends on
In the influence of wavelength, effect is indicated are as follows:
λ=λem·exp(-τλ″d)+n
In formula, τ is that degeneration factor, λ " are wavelength, and d is reflection sources to detecting devices distance, and n is extraneous noise；Imaging
In the process, the signal fallen on the detection apparatus indicates are as follows:
I (x, y)=λ (x, y)+λs(x, y)
λsFor detecting devices reflecting component, the pixel grey scale P (x, y) in imaging system is indicated are as follows:
P (x, y)=ζ I (x, y)+n (x, y)+ψ
Wherein, n (x, y) is that system introduces noise, and ζ is model gain coefficient, and ψ is the offset of signal；
Image carries out in enhancing processing, and user is waited for that site of puncture picture breakdown is multiple components, these component directions, position
It sets variant with size；User after decomposition waits for that the minutia of site of puncture image is indicated by high fdrequency component；Outside image
Contouring is indicated by low frequency component；User after site of puncture image adaptive enhancing algorithm in transformation after wavelet coefficient
It indicates are as follows:
The condition of above formula transformation results is respectively as follows:
ηin> ζ2、ζ1< ηin< ζ2、-ζ1≤ηin≤ζ2、-ζ2≤ηin≤ζ1、ηin<-ζ2；
Wherein, G gain factor, ζ1And ζ2For threshold value thresholding, the relationship of G and ζ are expressed as:
ζ1、ζ2Respectively threshold value, and meet ζ1< ζ2, when external noise is larger, the gain of wavelet coefficient is smaller；
It is larger to the gain of wavelet coefficient when external noise is smaller；While image effect enhancing, the dry of external noise is filtered out
It disturbs, during user waits for the imaging of site of puncture image, adds the signal made an uproar are as follows:
λt=λ nm+na
If f (x, y) is signal, n (x, y) is noise, and additive noise and multiplicative noise respectively indicate are as follows:
G (x, y)=f (x, y)+n (x, y)
G (x, y)=f (x, y) [1+n (x, y)]=f (x, y)+f (x, y) n (x, y)；
The Minimum Mean Square Error σ of original image2Are as follows:
Site of puncture image, which carries out Fourier transformation, to be waited for original user:
Wherein, φ (x, y) is filter transfer function, waits for that site of puncture image carries out at noise filtering to the user of acquisition
Reason:
Rf(x, y)=f (x, y) f (- x ,-y)
∫ ∫ f (i, j) (i+x, j+y) didj,
Rf(x, y)=n (x, y) n (- x ,-y)
∫ ∫ n (i, j) n (i+x, j+y) didj,
Pf(i, j)=F [Rf(x, y)],
Pn(i, j)=F [Rn(x, y)]
Pf(i, j) and Pn(i, j) is the power spectrum that original user waits for site of puncture image and noise, utilizes image data
Estimation and parameter complete the enhancing and denoising for the treatment of site of puncture image display effect.
To being carried out in enhancing processing operation to site of puncture image for acquisition, using the noise-reduction method based on MRF for dropping
It makes an uproar processing, using maximum a posteriori probability as optimization criterion, keeps the energy of the MRF model of building minimum；By Bayes formula into
Row maximum a-posteriori estimation maximizes following formula:
p(RV|IV, LV)∝p(IV|RV, LV)p(RV|LV)
In formula: IV、RV、LVThe brightness of respectively original image waits for that site of puncture image, brightness wait for that site of puncture image is corresponding
Reflecting component and luminance component；p(RV|LV) it is prior probability, the R that will be solved can be reflectedVThe property that should have；P(IV|
RV, LV) it is likelihood function, indicate the distribution that picture noise is obeyed；MAP target is found out under conditions of meeting maximum a posteriori probability
Estimated value to site of puncture image reflecting component；Maximum a posteriori probability problem is converted into minimum by log-likelihood function
The problem of its corresponding energy function:
Another object of the present invention is to provide the ultrasound guided puncture image procossing described in a kind of realize based on virtual reality
The computer program of method.
Another object of the present invention is to provide the ultrasound guided puncture image procossing described in a kind of realize based on virtual reality
The computer of method.
Another object of the present invention is to provide a kind of computer readable storage medium, including instruction, when its on computers
When operation, so that computer executes the ultrasound guided puncture image processing method based on virtual reality.
Another object of the present invention is to provide the ultrasound guided puncture image procossing described in a kind of realize based on virtual reality
The ultrasound guided puncture image processing system based on virtual reality of method, comprising:
Image capture module, by ultrasound guided puncture image capture module acquire user wait for site of puncture image data with
Image enhancement module connection waits for site of puncture image data for acquiring user by ultrasonic probe, carries out image enhancement, denoising
Processing waits for that site of puncture image carries out effect enhancing and denoising to collected user, highlights minutia；
Image enhancement module is connect with image capture module, central control module, for acquisition to site of puncture figure
As carrying out enhancing processing operation, noise reduction process is used for using the noise-reduction method based on MRF, using maximum a posteriori probability as optimization
Criterion keeps the energy of the MRF model of building minimum；
Central control module, with image capture module, image enhancement module, image conversion module, track navigation module, wear
Module, the connection of virtual display module are pierced, is worked normally for controlling modules；
Image conversion module, connect with central control module, and the image for that will acquire is made by three-dimensional software and converted
For three-dimensional scenic；
Track navigation module, connect with central control module, for determining the track punctured navigation；
Piercing module is connect with central control module, for confirming to user's operation station diagram picture；
Virtual display module, connect with central control module, for showing the virtual scene of site of puncture；
Described image conversion module includes model construction module, scene rendering module, scene identity module；
Model construction module, for constructing the three dimensional virtual models of site of puncture；
Scene rendering module, for carrying out scene rendering to the threedimensional model of building；
Scene identity module is identified for the three-dimensional virtual scene position to site of puncture.
Another object of the present invention is to provide the ultrasound guided puncture image procossing based on virtual reality described in a kind of carrying
The medical operating platform of system.
Advantages of the present invention and good effect are as follows:
The present invention emits deflection angle according to the frequency attribute of probe using ultrasonic wave by image enhancement module and is imaged special
Point setting simplifies operation it is therefore not necessary to which user intervention can also make the launch angle sequence generated more meet the attribute of probe itself
Step, and the more crucial image stream comprising needle body can be obtained according to the image stream that the launch angle sequence generates, to packet
After image stream containing needle body carries out denoising, fusion, the enhancing image of ultrasonic puncture needle is obtained, and the enhancing of ultrasonic puncture needle
Image is apparent, accurate, and the ultrasound image for subsequent accurate analysis user itself provides strong foundation；It is converted simultaneously by image
Module, virtual display module by virtual reality technology be applied to ultrasonic puncture operation in, enhance display three-dimensional sense and flexibly
Property, help the faster and better completion operation of doctor.
The present invention is solved in three-dimensional scenic cognitive network resource management process by mathematical space theory, by resource space
Between in establish resource status hypersurface, and available resource status vector is judged by constraint condition, further according to the available of formation
State hypersurface finds out optimal vector finally by resource allocation algorithm at available resources area of space, in available resources sky
Between middle selection performance best vector as the allocation result for meeting communication requirement, obtain accurate scene data.
Ultrasound guided puncture image processing method provided in an embodiment of the present invention based on virtual reality, comprising:
Acquisition user waits for site of puncture image data；Enhancing processing operation is carried out to the image of acquisition；
Three-dimensional scenic is converted by three-dimensional software production by the image of acquisition；It include: to be provided in three-dimensional scenic cognition network
The resource space model that source element is constituted
In, wherein Y indicates that 2D-FWHT becomes
The matrix of consequence changed, H4Indicate the coefficient matrix of 2D-FWHT transformation,Indicate H4Transposed matrix, X indicate candidate blocks data
The matrix of composition；
The resource that one-dimensional fast Hadamard transform indicates that cognition network system senses obtain is carried out with the form of state vector
State, one-dimensional fast Hadamard transform are as follows:
Wherein, Y indicates the matrix of consequence of 1D-FWHT transformation, H8Indicate that the coefficient matrix of 1D-FWHT transformation, X indicate candidate
Block number according to composition matrix；Three-dimensional denoising proposed by the present invention has reached high speed real-time de-noising, can get accurately three-dimensional
Contextual data.
Present invention determine that track navigation optimizing is carried out using the method for optimal path in the track navigation punctured,
1) bat individual is encoded based on the probability amplitude on the basis of basic bat algorithm using quantum bit, i.e. dosage
Sub- revolving door is updated the probability amplitude of quantum bit, is received using quantum non-gate as mutation operation to avoid the precocity of algorithm
It holds back；For each quantum bit tool, there are two probability amplitudes, and therefore, every bat can indicate two positions in optimization space；
In quantum calculation, the smallest information unit is stored in a quantum bit, and the state of the quantum bit may
For " 0 ", it is also possible to the free position between " 1 ", or " 0 " and " 1 "；The state of one quantum bit is expressed as follows:
| Ψ >=α | 0 >+β | 1 >.
By above-mentioned operational model, accurate image path information can get, provide accurate guide for ultrasound guided puncture
Meaning.
Detailed description of the invention
Fig. 1 is that the present invention implements the ultrasound guided puncture image processing method flow chart based on virtual reality provided.
Fig. 2 is that the present invention implements the ultrasound guided puncture image processing system block diagram based on virtual reality provided.
In figure: 1, image capture module；2, image enhancement module；3, central control module；4, image conversion module；5, rail
Mark navigation module；6, piercing module；7, virtual display module.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
With reference to the accompanying drawing and specific embodiment is further described application principle of the invention.
As shown in Figure 1, the ultrasound guided puncture image processing method provided in an embodiment of the present invention based on virtual reality, packet
Include following steps:
S101 acquires user by acquiring ultrasound image module and waits for site of puncture image data；Pass through image enhancement module
Enhancing processing operation is carried out to the image of acquisition to be used to wait for site of puncture image data by ultrasonic probe acquisition user, is used
Site of puncture image enhancement, denoising are waited in family, carry out effect enhancing and denoising to site of puncture image to collected,
To highlight its minutia；Noise is effectively inhibited, and the Edge Oscillation of image can be reduced, projecting edge details, final
To ideal reinforcing effect, is conducive to doctor and observes.
S102, central control module dispatch image conversion module and convert three by three-dimensional software production for the image of acquisition
Scene is tieed up, helps doctor to better understand user situation, reasonable analysing patient's condition effectively formulates puncturing schemes；
S103 determines that the track punctured is navigated by track navigation module；The rail punctured is determined by track navigation module
Mark navigation；And user's operation station diagram picture is confirmed by piercing module；
S104 shows the virtual scene of site of puncture by virtual display module.
As shown in Fig. 2, the ultrasound guided puncture image processing system provided in an embodiment of the present invention based on virtual reality, packet
Include: image capture module 1, central control module 3, image conversion module 4, track navigation module 5, punctures image enhancement module 2
Module 6, virtual display module 7.
Image capture module 1 is connect with image enhancement module 2, waits for site of puncture for acquiring user by ultrasonic probe
Image data；
Image enhancement module 2 is connect with image capture module 1, central control module 3, for the image progress to acquisition
Enhance processing operation；
Central control module 3, with image capture module 1, image enhancement module 2, image conversion module 4, track navigation mould
Block 5, piercing module 6, virtual display module 7 connect, and work normally for controlling modules；
Image conversion module 4 is connect with central control module 3, and the image for that will acquire is turned by three-dimensional software production
Turn to three-dimensional scenic；
Track navigation module 5 is connect with central control module 3, for determining the track punctured navigation；
Piercing module 6 is connect with central control module 3, for confirming to user's operation station diagram picture；
Virtual display module 7, connect, for showing the virtual scene of site of puncture with central control module 3.To create
Three-dimensional virtual scene and three-dimensional broadcasting, inquire into operation plan and carry out digitlization surgical simulation.
Image conversion module 4 provided by the invention includes model construction module, scene rendering module, scene identity module；
Model construction module, for constructing the three dimensional virtual models of site of puncture；
Scene rendering module, for carrying out scene rendering to the threedimensional model of building；
Scene identity module is identified for the three-dimensional virtual scene position to site of puncture.
2 Enhancement Method of image enhancement module provided by the invention is as follows:
Firstly, emitting deflection angle according to preset ultrasonic wave generates launch angle sequence, the preset ultrasonic wave transmitting
Deflection angle is arranged according to the frequency attribute and imaging characteristics of probe；
Secondly, generating the image stream of different attribute feature according to the launch angle sequence；
Then, described image stream is performed corresponding processing respectively according to the different attribute feature of image stream；
Finally, the image stream after fusion treatment, to obtain the enhancing image of ultrasonic puncture needle.
It is provided by the invention to be specifically included according to preset ultrasonic wave transmitting deflection angle generation launch angle sequence:
Predetermined angle difference threshold value；
Emit deflection angle and preset differential seat angle threshold value according to preset ultrasonic wave, generate launch angle sequence, generates
The differential seat angle of two neighboring launch angle be less than preset differential seat angle threshold value, preset ultrasonic wave transmitting deflection angle is adjacent thereto
Generation launch angle differential seat angle be less than preset differential seat angle threshold value.
Below with reference to concrete analysis, the invention will be further described.
Ultrasound guided puncture image processing method provided in an embodiment of the present invention based on virtual reality, comprising:
Acquisition user waits for site of puncture image data；Enhancing processing operation is carried out to the image of acquisition；
Three-dimensional scenic is converted by three-dimensional software production by the image of acquisition；It include: to be provided in three-dimensional scenic cognition network
The resource space model that source element is constituted
In, wherein Y indicates that 2D-FWHT becomes
The matrix of consequence changed, H4Indicate the coefficient matrix of 2D-FWHT transformation,Indicate H4Transposed matrix, X indicate candidate blocks data
The matrix of composition；
The resource that one-dimensional fast Hadamard transform indicates that cognition network system senses obtain is carried out with the form of state vector
State, one-dimensional fast Hadamard transform are as follows:
Wherein, Y indicates the matrix of consequence of 1D-FWHT transformation, H8Indicate that the coefficient matrix of 1D-FWHT transformation, X indicate candidate
Block number according to composition matrix；
And the hypersurface in multi dimensional resource space is constituted using the set that all resource status vectors are formed；And multidimensional is provided
Hypersurface in source space carries out threshold decision output；
Wherein, Y indicates hard -threshold processing result, and X indicates three-dimensional Hadamard transform as a result, Threshold expression judges threshold
Value, sigma indicate noise estimate variance；
One-dimensional inverse fast Hadamard transform, 2 dimension inverse fast Hadamard transforms are carried out after threshold decision output, obtain block estimation
As a result；
One-dimensional inverse fast Hadamard transform includes:
Wherein, Y indicates the matrix of consequence of 1D-IFWHT transformation, H8Indicate that the coefficient matrix of 1D-IFWHT transformation, X indicate hard
Threshold process result forms column vector；
2, which tie up inverse fast Hadamard transforms, includes:
Wherein, Y indicates the matrix of consequence of 2D-IFWHT transformation, H4Indicate the coefficient matrix of 2D-IFWHT transformation,It indicates
H4Transposed matrix, X indicates the matrix of one-dimensional inverse transformed result composition；
The constraint condition for judging resource status availability is formed according to the demand of communication service, and is sentenced with the constraint condition
Whether each state vector on disconnected resource status hypersurface meets the constraint condition, will select the qualified state come
Set of vectors constitutes available resources state hypersurface；
By the available resources state hypersurface of formation at all resource vectors for meeting constraint condition in resource space
Regional scope forms available resources space；
Resource allocation algorithm is set, and selects state optimal in the available resources space with the resource allocation algorithm
Vector；Obtain accurate three-dimensional scene images data.
The ultrasound guided puncture image processing method based on virtual reality further comprises:
Determine the track navigation punctured；User's operation station diagram picture is confirmed.
It determines in the track navigation punctured, track navigation optimizing is carried out using the method for optimal path, is specifically included:
1) bat individual is encoded based on the probability amplitude on the basis of basic bat algorithm using quantum bit, i.e. dosage
Sub- revolving door is updated the probability amplitude of quantum bit, is received using quantum non-gate as mutation operation to avoid the precocity of algorithm
It holds back；For each quantum bit tool, there are two probability amplitudes, and therefore, every bat can indicate two positions in optimization space；
2) in quantum calculation, the smallest information unit is stored in a quantum bit, and the state of the quantum bit can
Can be " 0 ", it is also possible to the free position between " 1 ", or " 0 " and " 1 "；The state of one quantum bit is expressed as follows:
| Ψ >=α | 0 >+β | 1 >
Wherein, α and β meets:
| α | 2+ | β | 2=1
Wherein, | α | 2 Hes | β | 2 respectively indicate and tend to state | 0 > and | 1 > probability；
One n member quantum bit are as follows:
Quantum rotating gate is as follows:
Quantum non-gate is as follows:
3) generate initial population: the encoding scheme of use is as follows:
Wherein, θ ij is argument, by formula (17) it can be seen that every bat has corresponded to two positions of problem space, respectively
Corresponded to quantum state | 0 > and | 1 > probability amplitude:
Pic=(cos (θ i1), cos (θ i2) ..., cos (θ in))
Pis=(sin (θ i1), sin (θ i2) ..., sin (θ in))
4) conversion of solution space:
To calculate the fitness of individual and evaluating the superiority and inferiority of individual, need to convert the solution space of population；
Each probability amplitude of the quantum bit of individual has corresponded to a solution of the solution space of problem, i.e., every bat has corresponded to optimization problem
Two solutions；
Wherein,By quantum state | 0 > probability amplitudeIt acquires, andBy quantum state | 1 > probability amplitudeIt obtains；
5) more new strategy:
In quantum bat algorithm (QBA), using bat algorithm (BA) more new strategy to the argument increment of quantum bit into
Row updates, and renewal process is as follows:
Δ θ ij (t+1)=Δ θ ij (t)+Δ θ g*Q (i) * stepnow
θ ij (t+1)=θ ij (t)+Δ θ ij (t+1)
Wherein, Δ θ ij and θ ij are respectively argument increment and argument；
Parameter value in formula is respectively as follows: w=2, σ e=0, σ s=2；
Probability amplitude is updated using Quantum rotating gate:
Obtain two new positions:
6) Mutation Strategy:
In quantum bat algorithm (QBA), algorithm prematurely falls into local optimum in order to prevent, uses Mutation Strategy herein
Increase the diversity of population, Mutation Strategy passes through quantum non-gate and realize；If rand () < pm, quantum non-gate behaviour is executed
Make, two probability values are exchanged；Wherein, pm is mutation probability；
The ultrasound guided puncture image processing method based on virtual reality further comprises:
Show the virtual scene of site of puncture.
Image method includes:
Firstly, emitting deflection angle according to preset ultrasonic wave generates launch angle sequence, the preset ultrasonic wave transmitting
Deflection angle is arranged according to the frequency attribute and imaging characteristics of probe；
Secondly, generating the image stream of different attribute feature according to the launch angle sequence；
Then, described image stream is performed corresponding processing respectively according to the different attribute feature of image stream；
Finally, the image stream after fusion treatment, to obtain the enhancing image of ultrasonic puncture needle；
Emit deflection angle generation launch angle sequence according to preset ultrasonic wave to specifically include:
Predetermined angle difference threshold value；
Emit deflection angle and preset differential seat angle threshold value according to preset ultrasonic wave, generate launch angle sequence, generates
The differential seat angle of two neighboring launch angle be less than preset differential seat angle threshold value, preset ultrasonic wave transmitting deflection angle is adjacent thereto
Generation launch angle differential seat angle be less than preset differential seat angle threshold value.
Further, acquisition user waits in site of puncture image data that image scene is by the reality with certain physics consistency
Body composition, the picture signal λ that entity issues1It indicates are as follows:
λ1=λ '+λr
Wherein, λ ' is radial component, λrFor reflecting component, since other subject matters also have light reflection in scene, on
Formula expands are as follows:
λ 1=λ '+λrs+λ0
λrsIt is degeneration factor, λ0For target reflecting component in scene, site of puncture image capturing system is waited for for user and
Speech, which is main component, and λrsIt is relatively small；From imaging is extracted degradation effect occurs for signal, and the degree of degeneration depends on
In the influence of wavelength, effect is indicated are as follows:
λ=λem·exp(-τλ″d)+n
In formula, τ is that degeneration factor, λ " are wavelength, and d is reflection sources to detecting devices distance, and n is extraneous noise；Imaging
In the process, the signal fallen on the detection apparatus indicates are as follows:
I (x, y)=λ (x, y)+λs(x, y)
λsFor detecting devices reflecting component, the pixel grey scale P (x, y) in imaging system is indicated are as follows:
P (x, y)=ζ I (x, y)+n (x, y)+ψ
Wherein, n (x, y) is that system introduces noise, and ζ is model gain coefficient, and ψ is the offset of signal；
Image carries out in enhancing processing, and user is waited for that site of puncture picture breakdown is multiple components, these component directions, position
It sets variant with size；User after decomposition waits for that the minutia of site of puncture image is indicated by high fdrequency component；Outside image
Contouring is indicated by low frequency component；User after site of puncture image adaptive enhancing algorithm in transformation after wavelet coefficient
It indicates are as follows:
The condition of above formula transformation results is respectively as follows:
ηin> ζ2、ζ1< ηin< ζ2、-ζ1≤ηin≤ζ2、-ζ2≤ηin≤ζ1、ηin<-ζ2；
Wherein, G gain factor, ζ1And ζ2For threshold value thresholding, the relationship of G and ζ are expressed as:
ζ1、ζ2Respectively threshold value, and meet ζ1< ζ2, when external noise is larger, the gain of wavelet coefficient is smaller；
It is larger to the gain of wavelet coefficient when external noise is smaller；While image effect enhancing, the dry of external noise is filtered out
It disturbs, during user waits for the imaging of site of puncture image, adds the signal made an uproar are as follows:
λt=λ nm+na
If f (x, y) is signal, n (x, y) is noise, and additive noise and multiplicative noise respectively indicate are as follows:
G (x, y)=f (x, y)+n (x, y)
G (x, y)=f (x, y) [1+n (x, y)]=f (x, y)+f (x, y) n (x, y)；
The Minimum Mean Square Error σ of original image2Are as follows:
Site of puncture image, which carries out Fourier transformation, to be waited for original user:
Wherein, φ (x, y) is filter transfer function, waits for that site of puncture image carries out at noise filtering to the user of acquisition
Reason:
Rf(x, y)=f (x, y) f (- x ,-y)
∫ ∫ f (i, j) (i+x, j+y) didj,
Rf(x, y)=n (x, y) n (- x ,-y)
∫ ∫ n (i, j) n (i+x, j+y) didj,
Pf(i, j)=F [Rf(x, y)],
Pn(i, j)=F [Rn(x, y)]
Pf(i, j) and Pn(i, j) is the power spectrum that original user waits for site of puncture image and noise, utilizes image data
Estimation and parameter complete the enhancing and denoising for the treatment of site of puncture image display effect.
To being carried out in enhancing processing operation to site of puncture image for acquisition, using the noise-reduction method based on MRF for dropping
It makes an uproar processing, using maximum a posteriori probability as optimization criterion, keeps the energy of the MRF model of building minimum；By Bayes formula into
Row maximum a-posteriori estimation maximizes following formula:
p(RV|IV, LV)∝p(IV|RV, LV)p(RV|LV)
In formula: IV、RV、LVThe brightness of respectively original image waits for that site of puncture image, brightness wait for that site of puncture image is corresponding
Reflecting component and luminance component；p(RV|LV) it is prior probability, the R that will be solved can be reflectedVThe property that should have；P(IV|
RV, LV) it is likelihood function, indicate the distribution that picture noise is obeyed；MAP target is found out under conditions of meeting maximum a posteriori probability
Estimated value to site of puncture image reflecting component；Maximum a posteriori probability problem is converted into minimum by log-likelihood function
The problem of its corresponding energy function:
In the above-described embodiments, can come wholly or partly by software, hardware, firmware or any combination thereof real
It is existing.When using entirely or partly realizing in the form of a computer program product, the computer program product include one or
Multiple computer instructions.When loading on computers or executing the computer program instructions, entirely or partly generate according to
Process described in the embodiment of the present invention or function.The computer can be general purpose computer, special purpose computer, computer network
Network or other programmable devices.The computer instruction may be stored in a computer readable storage medium, or from one
Computer readable storage medium is transmitted to another computer readable storage medium, for example, the computer instruction can be from one
A web-site, computer, server or data center pass through wired (such as coaxial cable, optical fiber, Digital Subscriber Line (DSL)
Or wireless (such as infrared, wireless, microwave etc.) mode is carried out to another web-site, computer, server or data center
Transmission).The computer-readable storage medium can be any usable medium or include one that computer can access
The data storage devices such as a or multiple usable mediums integrated server, data center.The usable medium can be magnetic Jie
Matter, (for example, floppy disk, hard disk, tape), optical medium (for example, DVD) or semiconductor medium (such as solid state hard disk Solid
State Disk (SSD)) etc..
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (10)
1. a kind of ultrasound guided puncture image processing method based on virtual reality, which is characterized in that described to be based on virtual reality
Ultrasound guided puncture image processing method include:
Acquisition user waits for site of puncture image data；Enhancing processing operation is carried out to the image of acquisition；
Image is carried out in enhancing processing, including converting three-dimensional scenic by three-dimensional software production for the image of acquisition；Specifically
Have: in the resource space model that three-dimensional scenic cognitive network resource element is constituted
In, wherein Y indicates 2D-FWHT transformation
Matrix of consequence, H4Indicate the coefficient matrix of 2D-FWHT transformation,Indicate H4Transposed matrix, X indicate candidate blocks data composition
Matrix；
The resource status that one-dimensional fast Hadamard transform indicates that cognition network system senses obtain is carried out with the form of state vector,
One-dimensional fast Hadamard transform are as follows:
Wherein, Y indicates the matrix of consequence of 1D-FWHT transformation, H8Indicate that the coefficient matrix of 1D-FWHT transformation, X indicate candidate block number
According to the matrix of composition；
And the hypersurface in multi dimensional resource space is constituted using the set that all resource status vectors are formed；And to multi dimensional resource sky
Between in hypersurface carry out threshold decision output；
Wherein, Y indicates hard -threshold processing result, and X indicates three-dimensional Hadamard transform as a result, Threshold indicates judgment threshold,
Sigma indicates noise estimate variance；
One-dimensional inverse fast Hadamard transform, 2 dimension inverse fast Hadamard transforms are carried out after threshold decision output, obtain block estimation knot
Fruit；
One-dimensional inverse fast Hadamard transform includes:
Wherein, Y indicates the matrix of consequence of 1D-IFWHT transformation, H8Indicate that the coefficient matrix of 1D-IFWHT transformation, X indicate hard -threshold
Processing result forms column vector；
2, which tie up inverse fast Hadamard transforms, includes:
Wherein, Y indicates the matrix of consequence of 2D-IFWHT transformation, H4Indicate the coefficient matrix of 2D-IFWHT transformation,Indicate H4's
Transposed matrix, X indicate the matrix of one-dimensional inverse transformed result composition；
The constraint condition for judging resource status availability is formed according to the demand of communication service, and judges money with the constraint condition
Whether each state vector on the state hypersurface of source meets the constraint condition, will select the qualified state vector come
Set constitutes available resources state hypersurface；
By the available resources state hypersurface of formation at all resource vector regions for meeting constraint condition in resource space
Range forms available resources space；
Resource allocation algorithm is set, and selects state optimal in the available resources space with the resource allocation algorithm and swears
Amount；Obtain accurate three-dimensional scene images data.
2. the ultrasound guided puncture image processing method based on virtual reality as described in claim 1, which is characterized in that described
Ultrasound guided puncture image processing method based on virtual reality further comprises:
Determine the track navigation punctured；User's operation station diagram picture is confirmed；It determines in the track navigation punctured, using most
The method of shortest path carries out track navigation optimizing, specifically includes:
1) it based on using the probability amplitude of quantum bit to encode bat individual on the basis of basic bat algorithm, i.e., is revolved with quantum
Revolving door is updated the probability amplitude of quantum bit, using quantum non-gate as mutation operation to avoid the Premature Convergence of algorithm；It is right
In each quantum bit tool, there are two probability amplitudes, and therefore, every bat can indicate two positions in optimization space；
2) in quantum calculation, the smallest information unit is stored in a quantum bit, and the state of the quantum bit may be
" 0 ", it is also possible to the free position between " 1 ", or " 0 " and " 1 "；The state of one quantum bit is expressed as follows:
| Ψ >=α | 0 >+β | 1 >
Wherein, α and β meets:
| α | 2+ | β | 2=1
Wherein, | α | 2 Hes | β | 2 respectively indicate and tend to state | 0 > and | 1 > probability；
One n member quantum bit are as follows:
Quantum rotating gate is as follows:
Quantum non-gate is as follows:
3) generate initial population: the encoding scheme of use is as follows:
Wherein, θ ij is argument, by formula (17) it can be seen that every bat has corresponded to two positions of problem space, is respectively corresponded
Quantum state | 0 > and | 1 > probability amplitude:
Pic=(cos (θ i1), cos (θ i2) ..., cos (θ in))
Pis=(sin (θ i1), sin (θ i2) ..., sin (θ in))
4) conversion of solution space:
To calculate the fitness of individual and evaluating the superiority and inferiority of individual, need to convert the solution space of population；Individual
Each probability amplitude of quantum bit corresponded to one of solution space solution of problem, i.e. every bat has corresponded to two of optimization problem
Solution；
Wherein,By quantum state | 0 > probability amplitudeIt acquires, andBy quantum state | 1 > probability amplitude?
It arrives；
5) more new strategy:
In quantum bat algorithm (QBA), the argument increment of quantum bit is carried out more using the more new strategy of bat algorithm (BA)
Newly, renewal process is as follows:
Δ θ ij (t+1)=Δ θ ij (t)+Δ θ g*Q (i) * stepnow
θ ij (t+1)=θ ij (t)+Δ θ ij (t+1)
Wherein, Δ θ ij and θ ij are respectively argument increment and argument；
Parameter value in formula is respectively as follows: w=2, σ e=0, σ s=2；
Probability amplitude is updated using Quantum rotating gate:
Obtain two new positions:
6) Mutation Strategy:
In quantum bat algorithm (QBA), algorithm prematurely falls into local optimum in order to prevent, is increased herein using Mutation Strategy
Add the diversity of population, Mutation Strategy is realized by quantum non-gate；If rand () < pm, quantum non-gate operation is executed, it will
Two probability values are exchanged；Wherein, pm is mutation probability；
3. the ultrasound guided puncture image processing method based on virtual reality as described in claim 1, which is characterized in that described
Ultrasound guided puncture image processing method based on virtual reality further comprises:
Show the virtual scene of site of puncture.
4. the ultrasound guided puncture image processing method based on virtual reality as described in claim 1, which is characterized in that
Image method includes:
Firstly, emitting deflection angle according to preset ultrasonic wave generates launch angle sequence, the preset ultrasonic wave transmitting turnover
Angle is arranged according to the frequency attribute and imaging characteristics of probe；
Secondly, generating the image stream of different attribute feature according to the launch angle sequence；
Then, described image stream is performed corresponding processing respectively according to the different attribute feature of image stream；
Finally, the image stream after fusion treatment, to obtain the enhancing image of ultrasonic puncture needle；
Emit deflection angle generation launch angle sequence according to preset ultrasonic wave to specifically include:
Predetermined angle difference threshold value；
Emit deflection angle and preset differential seat angle threshold value according to preset ultrasonic wave, generates launch angle sequence, the phase of generation
The differential seat angle of adjacent two launch angles is less than preset differential seat angle threshold value, the life adjacent thereto of preset ultrasonic wave transmitting deflection angle
At launch angle differential seat angle be less than preset differential seat angle threshold value.
5. the ultrasound guided puncture image processing method based on virtual reality as described in claim 1, which is characterized in that acquisition
User waits in site of puncture image data that image scene is made of the entity with certain physics consistency, the figure that entity issues
As signal λ1It indicates are as follows:
λ1=λ '+λr
Wherein, λ ' is radial component, λrFor reflecting component, since other subject matters also have light reflection in scene, above formula expands
Are as follows:
λ 1=λ '+λrs+λ0
λrsIt is degeneration factor, λ0It should for user waits for site of puncture image capturing system for target reflecting component in scene
Component is main component, and λrsIt is relatively small；From imaging is extracted degradation effect occurs for signal, and the degree of degeneration depends on wave
Long influence, effect indicate are as follows:
λ=λem·exp(-τλ″d)+n
In formula, τ is that degeneration factor, λ " are wavelength, and d is reflection sources to detecting devices distance, and n is extraneous noise；Imaging process
In, the signal fallen on the detection apparatus indicates are as follows:
I (x, y)=λ (x, y)+λs(x, y)
λsFor detecting devices reflecting component, the pixel grey scale P (x, y) in imaging system is indicated are as follows:
P (x, y)=ζ I (x, y)+n (x, y)+ψ
Wherein, n (x, y) is that system introduces noise, and ζ is model gain coefficient, and ψ is the offset of signal；
Image carries out in enhancing processing, by user wait for site of puncture picture breakdown be multiple components, these component directions, position and
Size is variant；User after decomposition waits for that the minutia of site of puncture image is indicated by high fdrequency component；The outer wheels of image
Exterior feature is indicated by low frequency component；In user, wavelet coefficient is indicated after the transformation in site of puncture image adaptive enhancing algorithm
Are as follows:
The condition of above formula transformation results is respectively as follows:
ηin> ζ2、ζ1< ηin< ζ2、-ζ1≤ηin≤ζ2、-ζ2≤ηin≤ζ1、ηin<-ζ2；
Wherein, G gain factor, ζ1And ζ2For threshold value thresholding, the relationship of G and ζ are expressed as:
ζ1、ζ2Respectively threshold value, and meet ζ1< ζ2, when external noise is larger, the gain of wavelet coefficient is smaller；Work as outside
It is larger to the gain of wavelet coefficient when noise is smaller；While image effect enhancing, the interference of external noise, user are filtered out
During to the imaging of site of puncture image, add the signal made an uproar are as follows:
λt=λ nm+na
If f (x, y) is signal, n (x, y) is noise, and additive noise and multiplicative noise respectively indicate are as follows:
G (x, y)=f (x, y)+n (x, y)
G (x, y)=f (x, y) [1+n (x, y)]=f (x, y)+f (x, y) n (x, y)；
The Minimum Mean Square Error σ of original image2Are as follows:
Site of puncture image, which carries out Fourier transformation, to be waited for original user:
Wherein, φ (x, y) is filter transfer function, waits for that site of puncture image carries out noise filtering processing to the user of acquisition:
Rf(x, y)=f (x, y) f (- x ,-y)
∫ ∫ f (i, j) (i+x, j+y) didj,
Rf(x, y)=n (xy) n (- x ,-y)
∫ ∫ n (i, j) n (i+x, j+y) didj,
Pf(i, j)=F [Rf(x, y)],
Pn(i, j)=F [Rn(x, y)]
Pf(i, j) and Pn(i, j) is the power spectrum that original user waits for site of puncture image and noise, utilizes the estimation of image data
And parameter, complete the enhancing and denoising for the treatment of site of puncture image display effect.
To being carried out in enhancing processing operation to site of puncture image for acquisition, using the noise-reduction method based on MRF at noise reduction
Reason keeps the energy of the MRF model of building minimum using maximum a posteriori probability as optimization criterion；It is carried out most by Bayes formula
Big posterior probability estimation maximizes following formula:
p(Rv|Iv, Lv)∞p(Iv|Rv, Lv)p(Rv|Lv)
In formula: Iv、Rv、LvThe brightness of respectively original image waits for that site of puncture image, brightness wait for the corresponding reflection of site of puncture image
Component and luminance component；p(Rv|Lv) it is prior probability, the R that will be solved can be reflectedvThe property that should have；P(Iv|Rv,
Lv) it is likelihood function, indicate the distribution that picture noise is obeyed；MAP target found out under conditions of meeting maximum a posteriori probability to
The estimated value of site of puncture image reflecting component；Maximum a posteriori probability problem is converted to by log-likelihood function and minimizes it
The problem of corresponding energy function:
6. a kind of ultrasound guided puncture image processing method realized described in Claims 1 to 5 any one based on virtual reality
Computer program.
7. a kind of ultrasound guided puncture image processing method realized described in Claims 1 to 5 any one based on virtual reality
Computer.
8. a kind of computer readable storage medium, including instruction, when run on a computer, so that computer is executed as weighed
Benefit requires the ultrasound guided puncture image processing method described in 1-5 any one based on virtual reality.
9. a kind of ultrasound guided puncture image processing method realized described in claim 1 based on virtual reality is showed based on virtual
Real ultrasound guided puncture image processing system, which is characterized in that at the ultrasound guided puncture image based on virtual reality
Reason system includes:
Image capture module acquires user by ultrasound guided puncture image capture module and waits for site of puncture image data and image
Enhance module connection, site of puncture image data is waited for for acquiring user by ultrasonic probe, at progress image enhancement, denoising
Reason waits for that site of puncture image carries out effect enhancing and denoising to collected user, highlights minutia；
Image enhancement module connect with image capture module, central control module, for acquisition to site of puncture image into
Row enhancing processing operation, is used for noise reduction process using the noise-reduction method based on MRF, and maximum a posteriori probability is quasi- as optimizing
Then, make the energy of the MRF model of building minimum；
Central control module, with image capture module, image enhancement module, image conversion module, track navigation module, puncture mould
Block, the connection of virtual display module, work normally for controlling modules；
Image conversion module, connect with central control module, for converting three by three-dimensional software production for the image of acquisition
Tie up scene；
Track navigation module, connect with central control module, for determining the track punctured navigation；
Piercing module is connect with central control module, for confirming to user's operation station diagram picture；
Virtual display module, connect with central control module, for showing the virtual scene of site of puncture；
Described image conversion module includes model construction module, scene rendering module, scene identity module；
Model construction module, for constructing the three dimensional virtual models of site of puncture；
Scene rendering module, for carrying out scene rendering to the threedimensional model of building；
Scene identity module is identified for the three-dimensional virtual scene position to site of puncture.
10. a kind of medical operating for carrying the ultrasound guided puncture image processing system based on virtual reality described in claim 1
Platform.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811136711.6A CN109330669A (en) | 2018-09-27 | 2018-09-27 | A kind of ultrasound guided puncture image processing system and method based on virtual reality |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110200648A (en) * | 2019-04-09 | 2019-09-06 | 田昕 | A kind of medical knee joint rehabilitation nursing system and information processing method |
| CN113910005A (en) * | 2021-09-10 | 2022-01-11 | 中国医学科学院北京协和医院 | Grinding system and signal processing method and device thereof |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103441956A (en) * | 2013-08-29 | 2013-12-11 | 西安电子科技大学 | Cognitive network resource management method based on resource space vector calculation |
| CN105761229A (en) * | 2016-03-15 | 2016-07-13 | 深圳市理邦精密仪器股份有限公司 | Ultrasonic puncture needle image enhance method and device |
| CN105976334A (en) * | 2016-05-06 | 2016-09-28 | 西安电子科技大学 | Three-dimensional filtering denoising algorithm based denoising processing system and method |
| CN106821499A (en) * | 2017-02-16 | 2017-06-13 | 清华大学深圳研究生院 | A kind of 3D virtual ultrasounds guided puncture navigation system and method |
| CN108501948A (en) * | 2018-04-16 | 2018-09-07 | 北京京大律业知识产权代理有限公司 | A kind of pilotless automobile control method based on virtual reality |
-
2018
- 2018-09-27 CN CN201811136711.6A patent/CN109330669A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103441956A (en) * | 2013-08-29 | 2013-12-11 | 西安电子科技大学 | Cognitive network resource management method based on resource space vector calculation |
| CN105761229A (en) * | 2016-03-15 | 2016-07-13 | 深圳市理邦精密仪器股份有限公司 | Ultrasonic puncture needle image enhance method and device |
| CN105976334A (en) * | 2016-05-06 | 2016-09-28 | 西安电子科技大学 | Three-dimensional filtering denoising algorithm based denoising processing system and method |
| CN106821499A (en) * | 2017-02-16 | 2017-06-13 | 清华大学深圳研究生院 | A kind of 3D virtual ultrasounds guided puncture navigation system and method |
| CN108501948A (en) * | 2018-04-16 | 2018-09-07 | 北京京大律业知识产权代理有限公司 | A kind of pilotless automobile control method based on virtual reality |
Non-Patent Citations (2)
| Title |
|---|
| 赵丽: "红外光图像采集及其特征提取技术的研究", 《激光杂志》 * |
| 赵宏宇: "马尔科夫随机场模型下的Retinex夜间彩色图像增强", 《光学精密工程》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110200648A (en) * | 2019-04-09 | 2019-09-06 | 田昕 | A kind of medical knee joint rehabilitation nursing system and information processing method |
| CN113910005A (en) * | 2021-09-10 | 2022-01-11 | 中国医学科学院北京协和医院 | Grinding system and signal processing method and device thereof |
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