CN204410840U - Renal artery removes sympathetic checkout gear - Google Patents
Renal artery removes sympathetic checkout gear Download PDFInfo
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- CN204410840U CN204410840U CN201420866741.3U CN201420866741U CN204410840U CN 204410840 U CN204410840 U CN 204410840U CN 201420866741 U CN201420866741 U CN 201420866741U CN 204410840 U CN204410840 U CN 204410840U
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Abstract
This utility model provides a kind of renal artery to remove sympathetic checkout gear, comprising: insertion type ultrasonic probe, supersonic imaging apparatus; Insertion type ultrasonic probe is connected with supersonic imaging apparatus; Insertion type supersonic imaging apparatus comprises: processor and memorizer; Processor is connected respectively with insertion type ultrasonic probe and memorizer.Use said apparatus can go sympathetic detection to renal artery, get the various image informations of sample segment, characteristic information and parameter preset.
Description
Technical field
This utility model relates to ultrasound detection field, particularly relates to a kind of renal artery and removes sympathetic checkout gear.
Background technology
Be widely used in clinical through tracheal tissue's ablation techniques, in the mechanotherapy of excessive activation relevant disease as sympathetic in arrhythmia, intractable hypertension etc.Ablation catheter is when realizing melting, and its principle produces a large amount of heat energy by transferring energy, is passed to the tissue around tunica adventitia, causes the neural degeneration outside blood vessel and in periadventitial tissue by tunica intima.
The hypertension common recognition in the current world, after fully and certainly looking back the clinical necessity of renal artery, proposes current arteriorenal challenge and is how to detect the success of operation in the preoperative with in art.In addition, not all patient is useful for this art, sum up think for the post-reacted parameter of predicting surgical and to operation in detect mode extremely important.
Because present renal artery goes sympathetic art just to carry out conventional angiography to preoperative, in art, cannot neurological condition be observed, postoperatively also cannot to confirm.Owing to comprehensively not observing the target that renal artery sympathetic nerve is namely performed the operation, evaluate and analyze, is therefore difficult to answer problem anxious to be resolved in the neural art application process of renal artery.
Be distributed in apart from the scope of about blood vessel center 1cm because the orthosympathetic diameter of renal artery is about about 200um, and the ultrasonic general imaging precision of existing Medical B is at about 1mm, special high-grade ultrasonic energy is to hundreds of micron.Also there is no this type of apparatus both at home and abroad at present, high investigation depth and high-resolution can be had simultaneously.
Given this, current treatment facility cannot get various image information or the characteristic information of sample segment.
Utility model content
This utility model provides a kind of renal artery to remove sympathetic checkout gear, uses this device can go sympathetic detection to renal artery, gets the various image informations of sample segment, characteristic information and parameter preset.
This utility model provides a kind of renal artery to remove sympathetic checkout gear, comprising:
Insertion type ultrasonic probe, supersonic imaging apparatus;
Described insertion type ultrasonic probe is connected with described supersonic imaging apparatus;
Described insertion type supersonic imaging apparatus comprises: processor, the first data base, the second data base, display;
Described processor is connected respectively with described insertion type ultrasonic probe, described first data base, described second data base and described display;
Wherein, described processor receives the echo-signal that described insertion type ultrasonic probe sends, described echo-signal is processed, obtain each orthosympathetic image information in described echo-signal and characteristic information and be stored in the second data base, described characteristic information is quantized, characteristic information after quantizing is mated with the presupposed information in the first data base, the parameter preset that presupposed information in acquisition the first data base that the match is successful is corresponding, and show described image information, characteristic information and parameter preset by described display.
Alternatively, described insertion type ultrasonic probe and described insertion type supersonic imaging apparatus are by tubes connection, and described insertion type ultrasonic probe device is in the front end of described conduit.
Alternatively, described insertion type ultrasonic probe comprises: insertion type high frequency monocrystal ultrasonic probe.
Alternatively, described insertion type ultrasonic probe comprises: insertion type array crystals ultrasonic probe.
Alternatively, described processor is flush bonding processor.
Alternatively, described display supports GTG display.
Alternatively, described display is liquid crystal display.
As shown from the above technical solution, renal artery of the present utility model is used to remove sympathetic checkout gear, can by the various image information of each sympathetic nerve of renal artery of ultra sonic imaging fetching portion sample, characteristic information and parameter preset.
Accompanying drawing explanation
Fig. 1 removes the structural representation of sympathetic checkout gear for renal artery that this utility model one embodiment provides;
The schematic flow sheet of Fig. 2 for using the renal artery of utility model shown in Fig. 1 to go sympathetic detection method.
Detailed description of the invention
Below in conjunction with drawings and Examples, detailed description of the invention of the present utility model is described in further detail.Following examples for illustration of this utility model, but are not used for limiting scope of the present utility model.
Fig. 1 removes the structural representation of sympathetic checkout gear for renal artery that this utility model one embodiment provides, and as shown in Figure 1, the renal artery of the present embodiment removes sympathetic checkout gear, comprising: described insertion type ultrasonic probe 1 is connected with described supersonic imaging apparatus 2;
Described insertion type supersonic imaging apparatus 2 comprises: processor 21, first data base 22, second data base 23, display 24;
Described processor 21 is connected respectively with described insertion type ultrasonic probe 1, described first data base 22, described second data base 23 and described display 24;
Wherein, described processor 21 receives the echo-signal that described insertion type ultrasonic probe 1 sends, described echo-signal is processed, obtain each orthosympathetic image information in described echo-signal and characteristic information and be stored in the second data base 23, described characteristic information is quantized, characteristic information after quantizing is mated with the presupposed information in the first data base 22, the parameter preset that presupposed information in acquisition the first data base 22 that the match is successful is corresponding, and show described image information, characteristic information and parameter preset by described display 24.
Wherein, described insertion type ultrasonic probe 1 is with described insertion type supersonic imaging apparatus 2 by tubes connection, and described insertion type ultrasonic probe 1 device is in the front end of described conduit.
For example, described insertion type ultrasonic probe 1 can be: insertion type high frequency monocrystal ultrasonic probe or insertion type array crystals ultrasonic probe;
Will be understood that, the high frequency monocrystal of described insertion type ultrasonic probe 1 or array crystals carry out the reception of hyperacoustic excitation and ultrasonic signal, synthesize ultrasonic two dimension or 3-D view, this monocrystal or array crystals device, in the front end of conduit, carry out ultrasound emission and reception in renal artery.
In a particular application, described processor 21 can be flush bonding processor.
In a particular application, described display 24 supports that GTG shows, and described display 24 can be liquid crystal display.
Use the renal artery of the present embodiment to remove the device of sympathetic detection, utilize ultra sonic imaging, sympathetic detection can be gone to renal artery, get the various image informations of sample segment, person's characteristic information and parameter preset.
In a practical application, use device described in the present embodiment, before renal artery ablative surgery by simulating completes, after renal artery blood vessel sample obtain renal artery ablative surgery before, after each sympathetic nerve image of renal artery, before renal artery ablative surgery, after the texture of each sympathetic nerve image of renal artery and changing features, can evaluate the effect of renal artery ablative surgery and feed back, the safety that renal artery goes sympathetic operation can be improved, the orthosympathetic distribution assessment in personalized Shen can be introduced, select the surgical parameters be more suitable for, the effectiveness that kidney goes sympathetic operation can be improved.
Fig. 2 shows the schematic flow sheet using the renal artery of utility model shown in Fig. 1 to go sympathetic detection method, as shown in Figure 2, the renal artery of the present embodiment goes sympathetic detection method as described below, and the method described in the present embodiment uses renal artery shown in Fig. 1 to remove sympathetic checkout gear.
201, obtain the echo-signal of ultrasonic probe, described echo-signal is that described ultrasonic probe launches hyperacoustic echo-signal to renal artery blood vessel to be detected.
It should be noted that the renal artery blood vessel to be detected of the present embodiment can be the renal artery blood vessel sample of simulation.
202, according to described echo-signal, orthosympathetic image information in described renal artery blood vessel is obtained.
It should be noted that obtained orthosympathetic image information is for two dimension or three-dimensional image information.
In a particular application, above-mentioned steps 202 can comprise not shown step 202a:
202a, amplitude and frequency processing are carried out to described echo-signal, obtain described orthosympathetic gray level image information.
In a particular application, after step 202a, also can comprise not shown step 202b-202e:
202b, the phase place of described echo-signal and frequency to be checked.
In a particular application, above-mentioned steps 202b can comprise:
Carried out envelope extraction to described by the echo-signal reflected, the frequency obtaining described echo-signal is strong and weak;
Carried out quadrature demodulation to described by the echo-signal reflected, obtain two orthogonal signalling each other, obtain two orthogonal signalling are divided by, extract the phase place of described echo-signal.
202c, to not in the same time, the echo-signal of the same degree of depth carries out autocorrelation analysis and Fourier transformation successively, obtains the frequency density spectral function of described echo-signal.
202d, frequency density spectral function according to described echo-signal, obtain the frequency displacement of described echo-signal, resolve the doppler imaging figure of described echo-signal.
202e, on the basis of described gray level image, superpose described doppler imaging figure, obtain orthosympathetic image information in described renal artery blood vessel.
Will be understood that, the basis of ordinary gamma image superposes doppler imaging figure and better can differentiate sympathetic nerve.
203, according to each orthosympathetic position, structural information, in described image information, extract each orthosympathetic characteristic information, and be stored in the second data base.
In a particular application, each orthosympathetic structural information can comprise: the density of sympathetic innervation, thickness, the degree of depth etc.
In a particular application, " according to each orthosympathetic position, structural information, extracting each orthosympathetic characteristic information in described image information " of above-mentioned steps 203, can comprise not shown step 203a-203b:
203a, remove the noise of described image information, described noise is speckle multiplicative noise.
Will be understood that, the object removing the noise of described image information is to improve signal to noise ratio to realize image enhaucament.
In a particular application, the noise of described image information is ultrasonic image noise, and it has obvious feature: visually see, ultrasonic image noise main manifestations is speckle noise; Noise Characteristic is analyzed, and ultrasonic noise main manifestations is multiplicative noise; So the noise of described image information is speckle multiplicative noise.
In an embody rule, in order to reach the object removing noise, can utilize the multiplicative feature of the noise of described image information, based on the method for small echo, above-mentioned steps 203a can comprise not shown step S1-S4:
S1, logarithmic transformation is carried out to described image, make multiplicative noise become additive noise.
S2, the image after logarithmic transformation is carried out multi-scale wavelet transformation, be the wavelet coefficient on multiple different scale by the picture breakdown after logarithmic transformation, described wavelet coefficient comprises: high-frequency wavelet coefficient and low-frequency wavelet coefficients.
S3, employing non-linear threshold filtering technique or soft-threshold technology process respectively to high-frequency wavelet coefficient and low-frequency wavelet coefficients, remove the noise coefficient part of the image after logarithmic transformation.
S4, the image after the logarithmic transformation after removing noise coefficient part is carried out wavelet inverse transformation, obtain the renal periarterial sympathetic nerve image after removing noise.
In an embody rule, in order to finally reach the object removing noise, full variation iterative can be utilized to restrain feature, and be optimized iteration to the energy function model built, above-mentioned steps 203a can comprise not shown step P1-P3:
P1, set up the noise model of described image.
P2, build the energy constraint equation of described noise model, described energy constraint equation comprises: two equations, and an equation is that another equation is for keeping image balance and noise smoothing for retaining picture characteristics and reducing the distortion factor.
P3, derive the iteration convergence equation of described energy constraint equation, by iteration, ask optimization solution, obtain the renal periarterial sympathetic nerve image after removing noise.
203b, according to each orthosympathetic position, structural information, extract each orthosympathetic characteristic information removing in the image information after noise, and set up the orthosympathetic feature information model of renal periarterial according to described characteristic information.
It should be noted that in the image information after removing noise of this step and extract each orthosympathetic characteristic information, refer to and identify Perivascular nerve fiber tissue, characteristic information extraction.First feature distribution and the structure of nervous tissue will be determined.In ultrasonic image, nervous tissue's distribution is within certain region of blood vessel, and occuping has nervous tissue within region, outside region, impassivity tissue distribution.Nervous tissue's imaging characteristic, on ultrasonic image, nervous tissue has some specific characteristic, such as highlighted, long and narrow, the low catoptric arrangement of interlayer etc.According to above characteristic information, the feature information model of nervous tissue can be set up.
204, described characteristic information is quantized, obtain quantized result.
In a particular application, above-mentioned steps 204 can comprise not shown step 204a and 204b:
204a, according to described characteristic information, splitting removing the image information after noise, obtaining the image information of target area parasympathetic tissue.
In an embody rule, above-mentioned steps 204a can comprise:
Extract the key message of the target area of described feature information model, set up feature templates;
Image after utilizing described feature templates to search for described removal noise, determines that the region matched with described feature templates is the region needing to split;
To the Image Segmentation Using after described removal noise, obtain the image information of target area parasympathetic tissue.
In another embody rule, above-mentioned steps 204a can comprise:
Predetermined threshold value information is utilized to filter the useless interfere information of major part and background information;
Horizontal histogram characteristic distributions in conjunction with described characteristic information gets rid of out of Memory, obtains the image information of target area parasympathetic tissue.
204b, the image information of described target area parasympathetic tissue to be quantized.
In an embody rule, above-mentioned steps 204b can comprise:
Multiple indexs in the image information of described target area parasympathetic tissue are measured, obtains multiple index result;
According to described multiple index result, obtain synthetical evaluating coefficient, described synthetical evaluating coefficient be after each index default evaluation coefficient corresponding with this index long-pending is added again with, each index correspondence default evaluation coefficient;
Described synthetical evaluating coefficient and default evaluation criterion are analyzed, obtain quantized result;
Wherein, describedly preset multiple index set and comprise: the length of nervous tissue, width, area and nervous tissue center are to the distance of blood vessel wall.
205, described quantized result is mated with the presupposed information in the first data base, the parameter preset that the acquisition presupposed information that the match is successful is corresponding.
Will be understood that, in actual applications, first data base of the present embodiment can be parametrization treatment data base, the parameter preset that presupposed information in this parametrization treatment data base is corresponding can be the parameter of renal artery ablative surgery, method according to the present embodiment, before renal artery ablative surgery, judge whether selected patients carries out renal artery ablative surgery according to quantized result, if selected patients carries out renal artery ablative surgery, surgical parameters can be selected according to extracted characteristic information in described default parametrization treatment data base.
The renal artery of the present embodiment goes the method for sympathetic detection, utilizes ultra sonic imaging, can go sympathetic detection to renal artery, gets the various image informations of sample segment, person's characteristic information and parameter preset.
Use method described in the present embodiment, renal artery ablative surgery by simulation completes forward and backward renal artery blood vessel sample and obtains the forward and backward each sympathetic nerve image of renal artery of renal artery ablative surgery, according to texture and the changing features of each sympathetic nerve image of the renal artery that renal artery ablative surgery is forward and backward, can evaluate the effect of renal artery ablative surgery and feed back.
In actual applications, use method described in the present embodiment, the safety that renal artery goes sympathetic operation can be improved, the orthosympathetic distribution assessment in personalized Shen can be introduced, select the surgical parameters be more suitable for, the effectiveness that kidney goes sympathetic operation can be improved.
Last it is noted that above each embodiment is only in order to illustrate the technical solution of the utility model, be not intended to limit; Although be described in detail this utility model with reference to foregoing embodiments, those of ordinary skill in the art is to be understood that: it still can be modified to the technical scheme described in foregoing embodiments, or carries out equivalent replacement to wherein some or all of technical characteristic; And these amendments or replacement, do not make the essence of appropriate technical solution depart from the scope of claim of the present utility model protection.
Claims (7)
1. renal artery removes a sympathetic checkout gear, it is characterized in that, comprising: insertion type ultrasonic probe, supersonic imaging apparatus;
Described insertion type ultrasonic probe is connected with described supersonic imaging apparatus;
Described insertion type supersonic imaging apparatus comprises: processor, the first data base, the second data base, display;
Described processor is connected respectively with described insertion type ultrasonic probe, described first data base, described second data base and described display;
Wherein, described processor receives the echo-signal that described insertion type ultrasonic probe sends, described echo-signal is processed, obtain each orthosympathetic image information in described echo-signal and characteristic information and be stored in the second data base, described characteristic information is quantized, characteristic information after quantizing is mated with the presupposed information in the first data base, the parameter preset that presupposed information in acquisition the first data base that the match is successful is corresponding, and show described image information, characteristic information and parameter preset by described display.
2. device according to claim 1, is characterized in that, described insertion type ultrasonic probe and described insertion type supersonic imaging apparatus are by tubes connection, and described insertion type ultrasonic probe device is in the front end of described conduit.
3. device according to claim 2, is characterized in that, described insertion type ultrasonic probe comprises: insertion type high frequency monocrystal ultrasonic probe.
4. device according to claim 2, is characterized in that, described insertion type ultrasonic probe comprises: insertion type array crystals ultrasonic probe.
5. device according to claim 1, is characterized in that, described processor is flush bonding processor.
6. device according to claim 1, is characterized in that, described display supports GTG display.
7. device according to claim 6, is characterized in that, described display is liquid crystal display.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201420866741.3U CN204410840U (en) | 2014-12-31 | 2014-12-31 | Renal artery removes sympathetic checkout gear |
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| CN201420866741.3U CN204410840U (en) | 2014-12-31 | 2014-12-31 | Renal artery removes sympathetic checkout gear |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113633283A (en) * | 2021-07-29 | 2021-11-12 | 上海安通医疗科技有限公司 | Interventional renal artery sympathetic nerve activity detection system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113633283A (en) * | 2021-07-29 | 2021-11-12 | 上海安通医疗科技有限公司 | Interventional renal artery sympathetic nerve activity detection system |
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| Date | Code | Title | Description |
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| C14 | Grant of patent or utility model | ||
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| TR01 | Transfer of patent right |
Effective date of registration: 20210701 Address after: 102200 building 7, 37 Chao Qian Road, Changping District, Beijing. Patentee after: Lepu Medical Technology (Beijing) Co.,Ltd. Address before: 102200 building 7, 37 Chaoqian Road, Changping Science and Technology Park, Changping District, Beijing Patentee before: Shanghai Shape Memory Alloy Co.,Ltd. Patentee before: Lepu Medical Technology (Beijing) Co.,Ltd. |
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| TR01 | Transfer of patent right |