CN106580371A - Doppler ultrasound blood flow detection device and detection method thereof - Google Patents
Doppler ultrasound blood flow detection device and detection method thereof Download PDFInfo
- Publication number
- CN106580371A CN106580371A CN201611121812.7A CN201611121812A CN106580371A CN 106580371 A CN106580371 A CN 106580371A CN 201611121812 A CN201611121812 A CN 201611121812A CN 106580371 A CN106580371 A CN 106580371A
- Authority
- CN
- China
- Prior art keywords
- blood flow
- energy
- pwr
- tissue
- signal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/06—Measuring blood flow
-
- A—HUMAN NECESSITIES
- 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
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Heart & Thoracic Surgery (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Pathology (AREA)
- Radiology & Medical Imaging (AREA)
- Biomedical Technology (AREA)
- Veterinary Medicine (AREA)
- Medical Informatics (AREA)
- Physics & Mathematics (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Hematology (AREA)
- Ultra Sonic Daignosis Equipment (AREA)
Abstract
The invention discloses a Doppler ultrasound blood flow detection device. The device comprises a wall filter 1, an autocorrelation processing module 1, a wall filter 2, an autocorrelation processing module 2, an energy gradient processing module, a blood flow detection module, a scanning conversion processing module, and a display module. The detection method for the Doppler ultrasound blood flow detection device comprises the following steps: determining preliminarily, measuring energy gradient (Pwr Chg); determining finally; performing blood flow signal scanning conversion processing; and performing composite display of blood flow and tissue signals. Under the condition that blood flow is preliminarily determined, the device needs to further measure the energy gradient (Pwr Chg), and the blood flow detection module finally determines blood flow or tissue through the energy gradient (Pwr Chg). The device can obviously reduce error rate of blood flow detection, and would not reduce sensitivity of blood flow detection of ultrasonic equipment.
Description
Technical field
Present invention relates particularly to a kind of Dopplcr ultrasound blood detection means and its detection method.
Background technology
The handling process of common colour doppler flow imaging is as shown in Figure 1.Ultrasonic blood after quadrature demodulation is obtained
After flow data, wall filter is sent to, with the energy of the tissue signal of low-speed motion of decaying.Wall filtering is carried out from phase after terminating
Pass is processed, and in the locus of each ultrasonic scan, average speed (Vel) and energy is estimated using the data after wall filtering
(Pwr).After the two supersonic blood relevant parameters are obtained, respectively the smoothing processing on room and time is carried out to these parameters
To remove noise, it is then fed into blood flow detection module using blood flow relevant parameter and B-mode image brightness (Env) to judge this
Position is tissue or blood flow.If the point value is then set to 0 by tissue, if blood flow is then set to Hemodynamic environment angle value.Then,
To representing the black-and-white signal of tissue and representing that the colour signal of blood flow is scanned conversion process, both signals are converted to directly
The signal of angular coordinate or polar coordinate system.Colour and black-and-white signal after conversion is being overlapped a two field picture by last display module
Middle display, if blood flow then shows colour signal according to blood flow rate, if tissue then shows black and white according to B-mode brightness
Signal.
In the handling process of color doppler ultrasonography, blood flow detection is a critically important module, its largely shadow
Ring blood flow sensitivity and the chromatic noise level of ultrasonic device.In common detection, the related ginseng of the blood flow that we use
Number and B-mode image brightness (Env) are come to judge current location be tissue or blood flow.The judgement of existing blood flow detection module
Logic is：
More than value is defined, then the point is tissue, is otherwise blood flow for B-mode image brightness (Env)；
Less than value is defined, then the point is tissue to average speed (Vel), is otherwise blood flow；
Less than value is defined, then the point is tissue to energy (Pwr), is otherwise blood flow；
If three above judged result is all blood flow, then the point is eventually judged to blood flow.
Such logical combination can distinguish tissue in most cases and blood flow, but work as and run into some special circumstances,
Then it is possible to detect mistake.
As shown in Fig. 2 left side is a kind of power spectrum chart of situation, the high part of energy is tissue, and low energy part is blood
Stream, if we arrange the wall filter that normalization cut-off frequency is 0.2, then we can obtain an energy after auto-correlation
Amount is higher, and normalization average speed is 0.4 signal.If the B-mode brightness (Env) and energy (Pwr) at the position
All meet the condition of blood flow of being judged as, and the threshold value of blood flow rate is if 0.25, then existing blood flow detection module can be very
Naturally current point is judged as blood flow.
But for the signal on the right side of Fig. 2, because the cut-off frequency of wall filter is 0.2, so some tissue
Signal arrives autocorrelative measure module by wall filter, so can also obtain that an energy comparison is high, and normalization is average
Speed is 0.3 signal.Under the conditions of same detection threshold value, existing blood flow detection module still can be judged as blood the point
Stream, but actually the point is a tissue motion signal, causes existing blood flow detection module to be made that the judgement of a mistake.
The content of the invention
It is an object of the invention to overcome the shortcoming of prior art, there is provided a kind of Dopplcr ultrasound blood detection means and its
Detection method, with solve it is aforementioned in particular cases, existing blood flow detection module error is judged as tissue motion signal
The problem of blood flow.
For achieving the above object, the technical solution used in the present invention is：
On the one hand, there is provided a kind of Dopplcr ultrasound blood detection means, including
Wall filter 1, for the tissue letter of low-speed motion in the supersonic blood data (IQ_Data) after the quadrature demodulation that decays
Number energy；
Auto-correlation processing module 1, in the locus of each ultrasonic scan, using the data after the process of wall filter 1
To determine average speed (Vel) and energy (Pwr)；
Also include
Wall filter 2, its cut-off frequency is different from wall filter 1, for the supersonic blood data after the quadrature demodulation that decays
(IQ_Data) energy of the tissue signal of low-speed motion in；
Auto-correlation processing module 2, using the data after the process of wall filter 2 energy (Pwr2) is determined；
Energy gradient processing module：The wall filter of different cut-off frequencies is determined using energy (Pwr2) and energy (Pwr)
Energy gradient (Pwr Chg) after ripple device 1 and the process of wall filter 2；
Blood flow detection module, it is bright using average speed (Vel) and energy (Pwr) after smoothing processing, and B-mode image
Degree (Env) and energy gradient (Pwr Chg) are tissue or blood flow and determine Hemodynamic environment angle value judging the position
(Vel1), and export represent tissue black-and-white signal and represent blood flow colour signal.
Preferably, also including
Scan conversion processing module, to representing the black-and-white signal of tissue and representing that the colour signal of blood flow is scanned conversion
Process, both signals are converted to into the signal of rectangular coordinate or polar coordinate system.
Preferably, also including
Display module, the expression tissue that scan conversion processing module is exported and the signal overlap of blood flow are in a two field picture
Show.
Preferably, also include smoothing module 1, the average speed (Vel) and energy to the output of auto-correlation processing module 1
Amount (Pwr) carries out the smoothing processing on room and time, to remove noise therein；
Smoothing module 2, to the energy (Pwr2) of the output of auto-correlation processing module 2 smoothing on room and time is carried out
Process to remove noise.
Preferably, the wall filter 1 and wall filter 2 are high pass filter.
Preferably, the cut-off frequency of the wall filter 2 is more than wall filter 1.
On the other hand, there is provided a kind of detection method of Dopplcr ultrasound blood detection means, comprise the following steps,
S1, preliminary judgement：
The tissue letter of low-speed motion in supersonic blood data (IQ_Data) after the decay quadrature demodulation of wall filter 1
Number energy；
By auto-correlation processing module 1 in the locus of each ultrasonic scan, using the number after the process of wall filter 1
According to determining average speed (Vel) and energy (Pwr)；
Blood flow detection module is using the average speed (Vel) after smoothing processing, energy (Pwr) and B-mode image brightness
(Env) come to judge the position be tissue or blood flow, its decision logic is as follows
B-mode image brightness (Env), is blood flow less than value is defined more than value is defined to organize；
Average speed (Vel), is blood flow more than value is defined less than value is defined to organize；
Energy (Pwr), is blood flow more than value is defined less than value is defined to organize；
All it is judged to organize or judge in B-mode brightness (Env), three numerical value of average speed (Vel) and energy (Pwr)
When inconsistent, the Hemodynamic environment angle value (Vel1) of the position is set to into 0, and exports the black-and-white signal for representing tissue；
Also include
S2, the measure of energy gradient (Pwr Chg)：
Average speed (Vel), energy (Pwr) and B-mode image brightness after blood flow detection module adopts smoothing processing
(Env) when being judged to blood flow, the measure of energy gradient (Pwr Chg) is carried out；
By the cut-off frequency wall filter 2 different from wall filter 1, the supersonic blood data after the quadrature demodulation that decays
(IQ_Data) energy of the tissue signal of low-speed motion in；
Auto-correlation processing module 2 determines energy (Pwr2) using the data after the process of wall filter 2；
Energy gradient processing module is determined the wall of different cut-off frequencies using energy (Pwr) and energy (Pwr2) and is filtered
Ripple device 1 and wall filter 2 process after energy gradient (Pwr Chg), it determines formula and is
S3, it is final to judge：
Blood flow detection module finally judges it is tissue or blood flow using energy gradient (Pwr Chg), and determines blood flow
Velocity amplitude (Vel1), its decision logic is as follows,
Energy gradient (Pwr Chg), is blood flow less than value is defined more than value is defined to organize；
When being judged to tissue, the Hemodynamic environment angle value (Vel1) of the position is set to into 0, and exports the black and white letter for representing tissue
Number；When being judged to blood flow, the Hemodynamic environment angle value (Vel1) of the position is set to into the average speed after smoothing processing (Vel), and it is defeated
Go out to represent the colour signal of blood flow.
Preferably, it is further comprising the steps of,
S4, the process of blood flow signal scan conversion：Scan conversion processing module is to representing the black-and-white signal of tissue and representing blood
The colour signal of stream is scanned conversion process, and both signals are converted to into the signal of rectangular coordinate or polar coordinate system.
Preferably, it is further comprising the steps of,
The synthesis of S5, blood flow and tissue signal shows：The expression tissue that display module exports scan conversion processing module
Show in a two field picture with the signal overlap of blood flow.
Preferably, in step S1, being carried out to average speed (Vel) and energy (Pwr) by smoothing module 1
Smoothing processing on room and time, to remove noise therein；
In step S2, the smoothing processing on room and time is carried out to energy (Pwr2) by smoothing module 2
To remove noise therein.
Beneficial effects of the present invention are：
1st, the present invention is judged in B-mode image brightness (Env), three data of average speed (Vel) and energy (Pwr)
In the case of blood flow, by wall filter 2, auto-correlation processing module 2, smoothing module 2 and energy gradient processing module
Determine energy gradient (Pwr Chg), blood flow detection module finally determined by energy gradient (Pwr Chg) be blood flow or
Tissue, can substantially reduce the error rate of blood flow detection, and the blood flow detection sensitivity of ultrasonic device will not be reduced again.
2nd, smoothing module 1 of the invention carries out flat on room and time to average speed (Vel) and energy (Pwr)
It is sliding to process, to remove noise therein, smoothing module 2 smoothing processing on room and time is carried out to energy (Pwr2) with
Noise is removed, can further optimizing detection data.
Description of the drawings
Fig. 1 is existing Dopplcr ultrasound blood detection method flow chart；
Fig. 2 is to be provided with the ultrasonic power spectrogram after wave filter 1；
Fig. 3 is the theory diagram of Dopplcr ultrasound blood detection means；
Fig. 4 is to be provided with the ultrasonic power spectrogram after wave filter 2.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with the specific embodiment of the invention and
Corresponding accompanying drawing is clearly and completely described to technical solution of the present invention.
Embodiment 1
With reference to Fig. 3, the present embodiment provides a kind of Dopplcr ultrasound blood detection means, including
Wall filter 1, for the tissue letter of low-speed motion in the supersonic blood data (IQ_Data) after the quadrature demodulation that decays
Number energy；
Auto-correlation processing module 1, in the locus of each ultrasonic scan, using the data after the process of wall filter 1
To determine average speed (Vel) and energy (Pwr)；
Also include
Wall filter 2, its cut-off frequency is different from wall filter 1, for the supersonic blood data after the quadrature demodulation that decays
(IQ_Data) energy of the tissue signal of low-speed motion in；
Auto-correlation processing module 2, using the data after the process of wall filter 2 energy (Pwr2) is determined；
Energy gradient processing module：The wall filter of different cut-off frequencies is determined using energy (Pwr2) and energy (Pwr)
Energy gradient (Pwr Chg) after ripple device 1 and the process of wall filter 2；
Blood flow detection module, it is bright using average speed (Vel) and energy (Pwr) after smoothing processing, and B-mode image
Degree (Env) and energy gradient (Pwr Chg) are tissue or blood flow and determine Hemodynamic environment angle value judging the position
(Vel1), and export represent tissue black-and-white signal and represent blood flow colour signal.
Also include
Scan conversion processing module, to representing the black-and-white signal of tissue and representing that the colour signal of blood flow is scanned conversion
Process, both signals are converted to into the signal of rectangular coordinate or polar coordinate system.
Also include
Display module, the expression tissue that scan conversion processing module is exported and the signal overlap of blood flow are in a two field picture
Show.
Also include smoothing module 1, the average speed (Vel) and energy (Pwr) of the output of auto-correlation processing module 1 are entered
Smoothing processing on row room and time, to remove noise therein；
Smoothing module 2, to the energy (Pwr2) of the output of auto-correlation processing module 2 smoothing on room and time is carried out
Process to remove noise.
The wall filter 1 and wall filter 2 are high pass filter.
The cut-off frequency of the wall filter 2 is more than wall filter 1.
Embodiment 2
With reference to Fig. 3, the present embodiment provides a kind of detection method of Dopplcr ultrasound blood detection means, including following step
Suddenly,
S1, preliminary judgement：
The tissue letter of low-speed motion in supersonic blood data (IQ_Data) after the decay quadrature demodulation of wall filter 1
Number energy；
By auto-correlation processing module 1 in the locus of each ultrasonic scan, using the number after the process of wall filter 1
According to determining average speed (Vel) and energy (Pwr)；
Blood flow detection module is using the average speed (Vel) after smoothing processing, energy (Pwr) and B-mode image brightness
(Env) come to judge the position be tissue or blood flow, its decision logic is as follows
B-mode image brightness (Env), is blood flow less than value is defined more than value is defined to organize；
Average speed (Vel), is blood flow more than value is defined less than value is defined to organize；
Energy (Pwr), is blood flow more than value is defined less than value is defined to organize；
All it is judged to organize or judge in B-mode brightness (Env), three numerical value of average speed (Vel) and energy (Pwr)
When inconsistent, the Hemodynamic environment angle value (Vel1) of the position is set to into 0, and exports the black-and-white signal for representing tissue；
Also include
S2, the measure of energy gradient (Pwr Chg)：
Average speed (Vel), energy (Pwr) and B-mode image brightness after blood flow detection module adopts smoothing processing
(Env) when being judged to blood flow, the measure of energy gradient (Pwr Chg) is carried out；
By the cut-off frequency wall filter 2 different from wall filter 1, the supersonic blood data after the quadrature demodulation that decays
(IQ_Data) energy of the tissue signal of low-speed motion in；
Auto-correlation processing module 2 determines energy (Pwr2) using the data after the process of wall filter 2；
Energy gradient processing module is determined the wall of different cut-off frequencies using energy (Pwr) and energy (Pwr2) and is filtered
Ripple device 1 and wall filter 2 process after energy gradient (Pwr Chg), it determines formula and is
S3, it is final to judge：
Blood flow detection module finally judges it is tissue or blood flow using energy gradient (Pwr Chg), and determines blood flow
Velocity amplitude (Vel1), its decision logic is as follows,
Energy gradient (Pwr Chg), is blood flow less than value is defined more than value is defined to organize；
When being judged to tissue, the Hemodynamic environment angle value (Vel1) of the position is set to into 0, and exports the black and white letter for representing tissue
Number；When being judged to blood flow, the Hemodynamic environment angle value (Vel1) of the position is set to into the average speed after smoothing processing (Vel), and it is defeated
Go out to represent the colour signal of blood flow.
It is further comprising the steps of,
S4, the process of blood flow signal scan conversion：Scan conversion processing module is to representing the black-and-white signal of tissue and representing blood
The colour signal of stream is scanned conversion process, and both signals are converted to into the signal of rectangular coordinate or polar coordinate system.
It is further comprising the steps of,
The synthesis of S5, blood flow and tissue signal shows：The expression tissue that display module exports scan conversion processing module
Show in a two field picture with the signal overlap of blood flow.
In step S1, by smoothing module 1 average speed (Vel) and energy (Pwr) are carried out space and when
Between on smoothing processing, to remove noise therein；
In step S2, the smoothing processing on room and time is carried out to energy (Pwr2) by smoothing module 2
To remove noise therein.
Explanation to embodiment 1 and 2：
If as shown in figure 4, have with Fig. 2 equal-wattages spectrum two groups of ultrasonic doppler data, by normalization cutoff frequency
Rate is 0.4 wall filter 2.So the average speed of left-side signal is 0.5；And right side because filtering be over after be all noise,
So energy can be than relatively low, but average speed (Vel) more a height of 0.65.If using conventional blood flow detection module to it is this this
Two kinds of situations are judged, if the value that defines of left side energy (Pwr) arranges reasonable, can correctly be adjudicated as blood flow, and right
Side can correctly be judged as tissue because energy is very low, also.But if the wall filtering of higher cutoff frequency is simply set merely
Device 2, most blood flow energy can be attenuated (as shown in Fig. 4 left sides), and this can cause the blood flow sensitivity of ultrasonic device bright
It is aobvious to lower.
The cartographic represenation of area energy of the closed area of swash and transverse axis.For the signal in left side, count after being filtered using wall filter 2
The energy of calculation is about the 50% of original blood flow energy, then energy gradient (Pwr Chg) is about 50%；And for right side letter
Number, after being filtered using wall filter 2, histokinesises' energy leached completely after only remaining noise, its energy is well below original
Histokinesises' energy, so its energy gradient (Pwr Chg) is close to 100%.The energy of the signal of the obvious left and right sides
Rate of change has significant difference.Energy gradient (Pwr Chg) this new parameter is delivered to into blood flow detection module synthesis to judge, can
Substantially to reduce the error rate of blood flow detection.
Be that energy gradient this new parameter arranges one and defines value in being embodied as, such as 70%, for using routinely
Blood flow detection method be detected as the signal of blood flow, can with 70%, this value of defining compare by its energy gradient (Pwr Chg)
Compared with, if greater than threshold value, then it is judged as tissue, if less than threshold value, then still it is judged as blood flow.
Therefore, the device employs energy gradient (Pwr Chg) this new parameter, can both increase the correct of detection
Rate, will not reduce the blood flow detection sensitivity of ultrasonic device again.
Above-mentioned embodiment is used for illustrating the present invention, rather than limits the invention, in the spirit of the present invention
In scope of the claims, any modifications and changes made to the present invention both fall within protection scope of the present invention.
Claims (10)
1. a kind of Dopplcr ultrasound blood detection means, including
Wall filter 1, for the tissue signal of low-speed motion in the supersonic blood data (IQ_Data) after the quadrature demodulation that decays
Energy；
Auto-correlation processing module 1, in the locus of each ultrasonic scan, is surveyed using the data after the process of wall filter 1
Determine average speed (Vel) and energy (Pwr)；
Characterized in that, also including
Wall filter 2, its cut-off frequency is different from wall filter 1, for the supersonic blood data (IQ_ after the quadrature demodulation that decays
Data the energy of the tissue signal of low-speed motion in)；
Auto-correlation processing module 2, using the data after the process of wall filter 2 energy (Pwr2) is determined；
Energy gradient processing module：The wall filter of different cut-off frequencies is determined using energy (Pwr2) and energy (Pwr)
1 and wall filter 2 process after energy gradient (Pwr Chg)；
Blood flow detection module, using average speed (Vel) and energy (Pwr) after smoothing processing, and B-mode image brightness
(Env) it is tissue or blood flow and determines Hemodynamic environment angle value (Vel1) judging the position with energy gradient (Pwr Chg),
And export the black-and-white signal for representing tissue and represent the colour signal of blood flow.
2. Dopplcr ultrasound blood detection means according to claim 1, it is characterised in that also include
Scan conversion processing module, to representing the black-and-white signal of tissue and representing that the colour signal of blood flow is scanned at conversion
Both signals are converted to the signal of rectangular coordinate or polar coordinate system by reason.
3. Dopplcr ultrasound blood detection means according to claim 1, it is characterised in that also include
Display module, the expression tissue that scan conversion processing module is exported and the signal overlap of blood flow show in a two field picture
Show.
4. Dopplcr ultrasound blood detection means according to claim 1, it is characterised in that also including smoothing module
1, the smoothing processing that the average speed (Vel) and energy (Pwr) exported to auto-correlation processing module 1 is carried out on room and time,
To remove noise therein；
Smoothing module 2, the smoothing processing on room and time is carried out to the energy (Pwr2) that auto-correlation processing module 2 is exported
To remove noise.
5. Dopplcr ultrasound blood detection means according to claim 1, it is characterised in that the wall filter 1 and wall
Wave filter 2 is high pass filter.
6. Dopplcr ultrasound blood detection means according to claim 1 or 5, it is characterised in that the wall filter 2
Cut-off frequency is more than wall filter 1.
7. a kind of detection method of Dopplcr ultrasound blood detection means, comprises the following steps,
S1, preliminary judgement：
The tissue signal of low-speed motion in supersonic blood data (IQ_Data) after the decay quadrature demodulation of wall filter 1
Energy；
By auto-correlation processing module 1 in the locus of each ultrasonic scan, come using the data after the process of wall filter 1
Determine average speed (Vel) and energy (Pwr)；
Blood flow detection module adopts the average speed (Vel) after smoothing processing, energy (Pwr) and B-mode image brightness (Env),
To judge that the position is tissue or blood flow, its decision logic is as follows
B-mode image brightness (Env), is blood flow less than value is defined more than value is defined to organize；
Average speed (Vel), is blood flow more than value is defined less than value is defined to organize；
Energy (Pwr), is blood flow more than value is defined less than value is defined to organize；
All it is judged to organize or judge to differ in B-mode brightness (Env), three numerical value of average speed (Vel) and energy (Pwr)
During cause, the Hemodynamic environment angle value (Vel1) of the position is set to into 0, and exports the black-and-white signal for representing tissue；
Characterized in that, also including
S2, the measure of energy gradient (Pwr Chg)：
Average speed (Vel), energy (Pwr) and B-mode image brightness (Env) after blood flow detection module adopts smoothing processing
When being judged to blood flow, the measure of energy gradient (Pwr Chg) is carried out；
By the cut-off frequency wall filter 2 different from wall filter 1, the supersonic blood data (IQ_ after the quadrature demodulation that decays
Data the energy of the tissue signal of low-speed motion in)；
Auto-correlation processing module 2 determines energy (Pwr2) using the data after the process of wall filter 2；
Energy gradient processing module determines the wall filter 1 of different cut-off frequencies using energy (Pwr) and energy (Pwr2)
With wall filter 2 process after energy gradient (Pwr Chg), its determine formula be
S3, it is final to judge：
Blood flow detection module finally judges it is tissue or blood flow using energy gradient (Pwr Chg), and determines blood flow rate
Value (Vel1), its decision logic is as follows,
Energy gradient (Pwr Chg), is blood flow less than value is defined more than value is defined to organize；
When being judged to tissue, the Hemodynamic environment angle value (Vel1) of the position is set to into 0, and exports the black-and-white signal for representing tissue；Sentence
When being set to blood flow, the Hemodynamic environment angle value (Vel1) of the position is set to into the average speed after smoothing processing (Vel), and exports expression
The colour signal of blood flow.
8. the detection method of Dopplcr ultrasound blood detection means according to claim 7, it is characterised in that also including following
Step,
S4, the process of blood flow signal scan conversion：Scan conversion processing module is to representing the black-and-white signal of tissue and representing blood flow
Colour signal is scanned conversion process, and both signals are converted to into the signal of rectangular coordinate or polar coordinate system.
9. the detection method of Dopplcr ultrasound blood detection means according to claim 7, it is characterised in that also including following
Step,
The synthesis of S5, blood flow and tissue signal shows：Expression tissue and blood that display module exports scan conversion processing module
The signal overlap of stream shows in a two field picture.
10. the detection method of Dopplcr ultrasound blood detection means according to claim 7, it is characterised in that the step
In S1, the smoothing processing on room and time is carried out to average speed (Vel) and energy (Pwr) by smoothing module 1, with
Remove noise therein；
In step S2, the smoothing processing on room and time is carried out to go to energy (Pwr2) by smoothing module 2
Except noise therein.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611121812.7A CN106580371B (en) | 2016-12-08 | 2016-12-08 | Doppler ultrasonic blood flow detection device and detection method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611121812.7A CN106580371B (en) | 2016-12-08 | 2016-12-08 | Doppler ultrasonic blood flow detection device and detection method thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106580371A true CN106580371A (en) | 2017-04-26 |
| CN106580371B CN106580371B (en) | 2023-06-27 |
Family
ID=58597444
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611121812.7A Active CN106580371B (en) | 2016-12-08 | 2016-12-08 | Doppler ultrasonic blood flow detection device and detection method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106580371B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108420457A (en) * | 2017-11-27 | 2018-08-21 | 苏州掌声医疗科技有限公司 | A kind of device of Dopplcr ultrasound blood gain-adjusted |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4095597A (en) * | 1975-03-05 | 1978-06-20 | Siemens Aktiengesellschaft | Arrangement for measuring cross-sectional fluctuations of conduits streamed through by fluids and for supplying indications of volumetric flow and/or conduit elasticity based thereon |
| US5431169A (en) * | 1992-08-03 | 1995-07-11 | Olympus Optical Co., Ltd. | Ultrasonic diagnosing apparatus |
| JPH08182676A (en) * | 1994-12-28 | 1996-07-16 | Toshiba Corp | Ultrasonic diagnostic device |
| CN1135712A (en) * | 1994-09-22 | 1996-11-13 | 勃勒柯研究有限公司 | Ultrasonic spectral contrast imaging |
| JP2001070305A (en) * | 1999-09-02 | 2001-03-21 | Matsushita Electric Ind Co Ltd | Sonograph |
| CN1559346A (en) * | 2004-03-01 | 2005-01-05 | 深圳迈瑞生物医疗电子股份有限公司 | Method and apparatus for post-processing of image of ultrasonic color blood flow |
| JP2005312773A (en) * | 2004-04-30 | 2005-11-10 | Toshiba Corp | Ultrasonic diagnostic apparatus |
| JP2005318921A (en) * | 2004-05-06 | 2005-11-17 | Aloka Co Ltd | Ultrasonic diagnostic equipment |
| US20060241460A1 (en) * | 2005-02-14 | 2006-10-26 | Fumio Kimura | Blood rheology measurement device and blood rheology measurement method |
| CN1917814A (en) * | 2004-02-05 | 2007-02-21 | 皇家飞利浦电子股份有限公司 | Ultrasonic imaging of perfusion and blood flow with harmonic contrast agents |
| US20100149920A1 (en) * | 2008-12-17 | 2010-06-17 | Medison Co., Ltd. | Clutter Signal Filtering For Doppler Signal |
| CN104883981A (en) * | 2013-01-23 | 2015-09-02 | 株式会社东芝 | Ultrasonic diagnostic device, image processing device, and image processing method |
| CN105590315A (en) * | 2015-12-04 | 2016-05-18 | 南京云石医疗科技有限公司 | Ultrasonic color Doppler image post-processing method |
-
2016
- 2016-12-08 CN CN201611121812.7A patent/CN106580371B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4095597A (en) * | 1975-03-05 | 1978-06-20 | Siemens Aktiengesellschaft | Arrangement for measuring cross-sectional fluctuations of conduits streamed through by fluids and for supplying indications of volumetric flow and/or conduit elasticity based thereon |
| US5431169A (en) * | 1992-08-03 | 1995-07-11 | Olympus Optical Co., Ltd. | Ultrasonic diagnosing apparatus |
| CN1135712A (en) * | 1994-09-22 | 1996-11-13 | 勃勒柯研究有限公司 | Ultrasonic spectral contrast imaging |
| JPH08182676A (en) * | 1994-12-28 | 1996-07-16 | Toshiba Corp | Ultrasonic diagnostic device |
| JP2001070305A (en) * | 1999-09-02 | 2001-03-21 | Matsushita Electric Ind Co Ltd | Sonograph |
| CN1917814A (en) * | 2004-02-05 | 2007-02-21 | 皇家飞利浦电子股份有限公司 | Ultrasonic imaging of perfusion and blood flow with harmonic contrast agents |
| CN1559346A (en) * | 2004-03-01 | 2005-01-05 | 深圳迈瑞生物医疗电子股份有限公司 | Method and apparatus for post-processing of image of ultrasonic color blood flow |
| JP2005312773A (en) * | 2004-04-30 | 2005-11-10 | Toshiba Corp | Ultrasonic diagnostic apparatus |
| JP2005318921A (en) * | 2004-05-06 | 2005-11-17 | Aloka Co Ltd | Ultrasonic diagnostic equipment |
| US20060241460A1 (en) * | 2005-02-14 | 2006-10-26 | Fumio Kimura | Blood rheology measurement device and blood rheology measurement method |
| US20100149920A1 (en) * | 2008-12-17 | 2010-06-17 | Medison Co., Ltd. | Clutter Signal Filtering For Doppler Signal |
| CN104883981A (en) * | 2013-01-23 | 2015-09-02 | 株式会社东芝 | Ultrasonic diagnostic device, image processing device, and image processing method |
| CN105590315A (en) * | 2015-12-04 | 2016-05-18 | 南京云石医疗科技有限公司 | Ultrasonic color Doppler image post-processing method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108420457A (en) * | 2017-11-27 | 2018-08-21 | 苏州掌声医疗科技有限公司 | A kind of device of Dopplcr ultrasound blood gain-adjusted |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106580371B (en) | 2023-06-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102319064B (en) | Device and method for improving accuracy of recognizing deceleration of fetal heart rate data | |
| CN106846344B (en) | A kind of image segmentation optimal identification method based on the complete degree in edge | |
| CN102319063B (en) | Device and method for improving acceleration identification accuracy of fetal heart rate data | |
| JP5121389B2 (en) | Ultrasonic diagnostic apparatus and method for measuring the size of an object | |
| CN105427342B (en) | A kind of underwater Small object sonar image target detection tracking method and system | |
| CN105662474B (en) | Automatic detection method and detection system for fetal head circumference ultrasonic image | |
| CN104036516B (en) | Camera calibration checkerboard image angular-point detection method based on symmetrical analysis | |
| CN107292835B (en) | Method and device for automatically vectorizing retinal blood vessels of fundus image | |
| KR20030074414A (en) | Image processing unit and ultrasonic diagnostic device | |
| CN107256406A (en) | Overlapping fibers image partition method, device, storage medium and computer equipment | |
| CN105737909A (en) | Anti-instantaneous-impact-interference signal processing method and system for vortex shedding flowmeter based on Kalman filtering | |
| CN102928435A (en) | Aircraft skin damage identification method and device based on image and ultrasound information fusion | |
| CN103226829A (en) | Image edge detection method based on edge enhancement operator | |
| US11257301B2 (en) | Image analysis apparatus, image analysis method, and image analysis program | |
| CN109345524A (en) | A kind of bearing open defect detection system of view-based access control model | |
| CN108090486A (en) | Image processing method and device in a kind of game of billiards | |
| CN107233109A (en) | A kind of Dopplcr ultrasound blood detecting system and its detection method | |
| CN106708009A (en) | Ship dynamic positioning measurement system multiple-fault diagnosis method based on support vector machine clustering | |
| CN106580371A (en) | Doppler ultrasound blood flow detection device and detection method thereof | |
| CN206745378U (en) | A kind of Dopplcr ultrasound blood detecting system | |
| CN109009216A (en) | A kind of ultrasonic image naked eye 3D system | |
| CN116152158A (en) | Weld joint detection method and device, electronic equipment and storage medium | |
| CN105953850B (en) | The small flow quantity detecting system of the online fluid of suspended body flowmeter and method based on machine vision | |
| JP3662835B2 (en) | Ultrasonic diagnostic equipment | |
| CN115409768A (en) | Water leakage disease deep learning detection method based on characteristic input enhancement |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |