CN113679418A - Ultrasonic imaging method based on compressed signal-to-noise ratio coefficient weighting - Google Patents
Ultrasonic imaging method based on compressed signal-to-noise ratio coefficient weighting Download PDFInfo
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- 238000003384 imaging method Methods 0.000 title claims abstract description 123
- 239000013598 vector Substances 0.000 claims abstract description 27
- 230000006835 compression Effects 0.000 claims abstract description 19
- 238000007906 compression Methods 0.000 claims abstract description 19
- 239000000523 sample Substances 0.000 claims abstract description 6
- 238000000034 method Methods 0.000 claims description 11
- 238000010606 normalization Methods 0.000 claims description 2
- 230000001629 suppression Effects 0.000 description 5
- 230000007547 defect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000012285 ultrasound imaging Methods 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001934 delay Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10132—Ultrasound image
Abstract
The invention discloses a high-quality ultrasonic imaging method based on compressed signal-to-noise ratio coefficient weighting, which comprises the steps of firstly storing echo signals received by an ultrasonic probe after time delay into a vector, then calculating a high-sensitivity signal-to-noise ratio coefficient of the vector, adjusting and outputting the coefficient into a compressed signal-to-noise ratio coefficient through a compression adjusting function, and finally multiplying the coefficient by an imaging result output by a beam former in an ultrasonic imaging system to obtain an image with high contrast and high resolution. The invention can restrain stronger noise and has little loss to the imaging intensity, thereby obtaining the ultrasonic image with high resolution and high contrast.
Description
Technical Field
The invention is suitable for the field of medical ultrasonic imaging, and particularly relates to a high-quality ultrasonic imaging method based on compressed signal-to-noise ratio coefficient weighting.
Background
Medical ultrasonic imaging equipment is one of the commonly used imaging equipment and has important value in diagnosis of many important diseases. In the medical ultrasonic imaging process, an ultrasonic probe firstly transmits ultrasonic waves to enter an imaging area, then receives echo signals scattered back by the imaging area, then determines the echo signals of imaging points according to the spatial position of each imaging point in the spatial area, then delays the echo signals to obtain imaging vectors, and the imaging vectors are directly superposed to obtain an imaging result. The imaging method of direct superposition has the defects of low resolution, low contrast ratio and the like. The high-quality ultrasonic imaging method is the core technology of the medical ultrasonic imaging equipment. The imaging method based on coefficient weighting is the commonly used imaging method for improving the ultrasonic imaging quality at present. The method designs a weighting coefficient according to the characteristics of the imaging vector, weights the directly superposed imaging result and improves the imaging quality. The current common weighting coefficients are mainly coherence coefficients designed according to coherence characteristics. Although the coherence coefficient weighted imaging method has a good imaging noise suppression capability, the resolution and contrast are still not sufficiently improved. Although the signal-to-noise ratio coefficient weighting imaging method has higher resolution, the imaging intensity is reduced, and the improvement of the contrast is limited.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides the ultrasonic imaging method based on the weighting of the compressed signal-to-noise ratio coefficient, so that the image noise can be effectively inhibited, the loss of the imaging intensity is little, and the ultrasonic image with high resolution and high contrast is obtained, thereby improving the imaging quality of the ultrasonic imaging system.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention relates to an ultrasonic imaging method based on compressed signal-to-noise ratio coefficient weighting, which is characterized by comprising the following steps:
the method comprises the following steps: in the ultrasonic imaging process, an ultrasonic probe is used for obtaining an echo signal of each imaging point in an original image and carrying out time delay to obtain an imaging vector of each imaging point, and then intensity values in the imaging vector of each imaging point are summed to respectively obtain an imaging result of each imaging point;
step two: respectively carrying out normalization processing on the imaging vector of each imaging point, and then calculating the mean value and the standard deviation of the imaging vector of each imaging point, so as to calculate the high-sensitivity signal-to-noise ratio coefficient of each imaging point according to the standard deviation and the mean value;
step three: establishing a compression adjustment function for carrying out compression adjustment on the high-sensitivity signal-to-noise ratio coefficient and obtaining a compression signal-to-noise ratio coefficient of each imaging point;
step four: multiplying the compression signal-to-noise ratio coefficient of each imaging point with the corresponding imaging result respectively to obtain a weighted imaging result of each imaging point;
step five: and performing graying processing on the weighted imaging results of all the imaging points to obtain a high-quality ultrasonic image.
The high sensitive signal-to-noise ratio coefficient SF in the step twohIs obtained by using a formula (1):
in the formula (1), μ is the mean value of the imaging vector of any imaging point, and represents the intensity of an effective signal in the imaging vector; and sigma is the standard deviation of the imaging vector of any imaging point and represents the intensity of noise in the imaging vector.
The compression adjustment function in step three is shown as formula (2):
in the formula (2), f (SF)h) Representing the compressed signal-to-noise ratio coefficient.
Compared with the prior art, the invention has the beneficial effects that:
the compressed signal-to-noise ratio coefficient in the invention can effectively identify the noise and the clutter in the imaging area, the value of the compressed signal-to-noise ratio coefficient of the noise and the clutter is lower, and the value of the compressed signal-to-noise ratio coefficient of the effective signal is higher. The compressed signal-to-noise ratio coefficient has excellent noise suppression capability, can effectively suppress clutter and noise, and keeps the strength of an effective signal. The compressed signal-to-noise ratio coefficient is multiplied by the directly superposed ultrasonic imaging result to obtain an ultrasonic image with high contrast and high resolution, and the compressed signal-to-noise ratio coefficient has a certain clinical application value.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a graph of input versus output for a compression key function of the present invention;
FIG. 3 is a diagram of the results of direct overlay imaging of simulated scattering sites of the present invention;
FIG. 4 is a graph of the compressed SNR coefficient weighted imaging result of a simulated scattering point according to the present invention;
FIG. 5 is a diagram of the results of direct overlay imaging of simulated circular spots of the present invention;
FIG. 6 is a graph of the compressed SNR coefficient weighted imaging result of the simulated circular spot of the present invention.
Detailed Description
In this embodiment, as shown in fig. 1, an ultrasound imaging method based on compressed snr coefficient weighting includes:
the method comprises the following steps: setting the echo signal at the position of a p point in an imaging area received by the nth array element in the ultrasonic probe and delaying the echo signal to obtain a signal value vn(p) to obtain an imaging vector v (p) ═ v1(p),v2(p),…,vn(p),…,vN(p)]And N represents the total number of receiving array elements, and the ultrasonic imaging result I (p) with directly superposed p points is calculated by using the formula (1):
step two: normalizing the imaging vector by using the formula (2) to obtain a normalized imaging vector V' (p):
calculating the high sensitive signal-to-noise ratio coefficient SF of the p point by using the formula (3)h(p)：
In the formula (3), E [. cndot. ] represents the mean value, and σ [. cndot. ] represents the standard deviation value. The formula (3) can improve the noise suppression capability by taking the signal-to-noise ratio coefficient to the power of 3.
Step three: the designed compression adjustment function is shown in equation (4). The compression function can compress the value of the input variable X to be between 0 and 1. The function input-output relationship is shown in fig. 2.
The high sensitive signal-to-noise ratio coefficient SFh(p) into the compression adjustment function to obtain the compression SNR coefficient f (SF) using equation (5)h)：
For imaging vectors with noise as the main component, SF for imaging vectors with noise as the main componenthHas stronger suppression capability compared with the traditional signal-to-noise ratio coefficient. However, for imaging vectors with significant signal as the main component, SFhThe estimated value of (c) may be too high, resulting in a deviation of the imaging result. The compressed SNR coefficient after the adjustment of the compression function keeps the noise suppression capability of the high sensitive SNR coefficient and works as SFhWhen the estimated value is too high, compression adjustment is performed, and image distortion is avoided.
Step five: the obtained weighting coefficient f (SF)h) Multiplying the direct imaging result I (p) to obtain a weighted imaging result I (p point position) by using the formula (6)f(p)：
If(p)＝f(SFh(p))×I(p) (6)
Repeating the first step to the fourth step on each point in the imaging area to obtain an imaging result I of the whole imaging areaf. Will IfAnd obtaining the high-quality ultrasonic image after logarithmic compression and graying.
Examples
In this embodiment, a simulation ultrasound imaging system is first established, and the system uses a 128-element linear array probe. The center frequency of the transmitted signal is 5MHz, and the sampling frequency of the system is 80 MHz. The sound velocity of the imaging area is 1540m/s, the focal depth is 40mm, and the effective array element number during imaging of each scanning line is 64. In order to verify the effectiveness of the algorithm, Gaussian white noise with certain intensity is added to the simulated echo signal. There are two imaging targets, one is scattering points of two strong echoes with a spacing of 14mm, the size of the imaging area is 10mm × 5mm, the coordinates of the imaging points are (-0.7mm, 25.5mm) and (0.7mm, 25.5mm), respectively, and the imaging results are shown in fig. 3. Another object is a simulated sound absorbing circular patch. The imaging area was 10mm x 9mm, the diameter inside the circular spot was 4mm, and the depth was 30mm, and the imaging results are shown in fig. 4.
Fig. 3 is the result of conventional direct overlay imaging, and it can be seen that there is significant noise in the background, which makes it difficult to distinguish between two imaging points due to poor resolution. Fig. 4 is an imaging result after weighting by the compressed snr coefficient, and it can be seen that the background noise is significantly reduced, the resolution of two points is significantly improved, and the two points can be accurately distinguished.
Fig. 5 is a direct superposition imaging result of the sound absorption circular spot, which shows that the noise in the circular spot is large and the contrast is poor. Fig. 6 is a result obtained by multiplying the directly superimposed imaging result by the compressed snr coefficient, and it can be seen that the noise inside the circular spot is removed, and the contrast between the circular spot and the background tissue is significantly improved.
Claims (3)
1. An ultrasonic imaging method based on compressed signal-to-noise ratio coefficient weighting is characterized by comprising the following steps:
the method comprises the following steps: in the ultrasonic imaging process, an ultrasonic probe is used for obtaining an echo signal of each imaging point in an original image and carrying out time delay to obtain an imaging vector of each imaging point, and then intensity values in the imaging vector of each imaging point are summed to respectively obtain an imaging result of each imaging point;
step two: respectively carrying out normalization processing on the imaging vector of each imaging point, and then calculating the mean value and the standard deviation of the imaging vector of each imaging point, so as to calculate the high-sensitivity signal-to-noise ratio coefficient of each imaging point according to the standard deviation and the mean value;
step three: establishing a compression adjustment function for carrying out compression adjustment on the high-sensitivity signal-to-noise ratio coefficient and obtaining a compression signal-to-noise ratio coefficient of each imaging point;
step four: multiplying the compression signal-to-noise ratio coefficient of each imaging point with the corresponding imaging result respectively to obtain a weighted imaging result of each imaging point;
step five: and performing graying processing on the weighted imaging results of all the imaging points to obtain a high-quality ultrasonic image.
2. The method as claimed in claim 1, wherein the second step is an ultrasonic imaging method based on weighting of SNR coefficient, wherein the second step is a high sensitive SNR coefficient SFhIs obtained by using a formula (1):
in the formula (1), μ is the mean value of the imaging vector of any imaging point, and represents the intensity of an effective signal in the imaging vector; and sigma is the standard deviation of the imaging vector of any imaging point and represents the intensity of noise in the imaging vector.
3. The method as claimed in claim 1, wherein the compression adjustment function in step three is shown as equation (2):
in the formula (2), f (SF)h) Representing the compressed signal-to-noise ratio coefficient.
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| CN110622034A (en) * | 2017-05-11 | 2019-12-27 | 皇家飞利浦有限公司 | Reverberation artifact cancellation in ultrasound diagnostic images |
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| US20070196008A1 (en) * | 2006-02-08 | 2007-08-23 | Anja Borsdorf | Method for noise reduction in tomographic image data records |
| CN105982694A (en) * | 2015-01-27 | 2016-10-05 | 无锡祥生医学影像有限责任公司 | Signal processing method for inhibiting ultrasonic noises |
| CN106780407A (en) * | 2017-03-01 | 2017-05-31 | 成都优途科技有限公司 | A kind of denoising system and denoising method for ultrasound pattern speckle noise |
| CN110622034A (en) * | 2017-05-11 | 2019-12-27 | 皇家飞利浦有限公司 | Reverberation artifact cancellation in ultrasound diagnostic images |
| CN107843305A (en) * | 2017-10-31 | 2018-03-27 | 合肥工业大学 | A kind of Ultrasonic Wave Flowmeter signal processing method based on echo signal envelope fitting |
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