CN102435992A - Synthetic Focusing Imaging Method Based on Generalized Coherence Coefficient - Google Patents
Synthetic Focusing Imaging Method Based on Generalized Coherence Coefficient Download PDFInfo
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Abstract
The invention discloses a synthetic focusing imaging method based on generalized coherence coefficients, which relates to the technical field of ultrasonic imaging, and aims at the characteristics of synthetic focusing data to perform double generalized coherence coefficient algorithm processing on echo data, wherein first generalized coherence coefficients are calculated for data received by all receiving array elements after a single transmitting array element transmits; then, weighting the summed received data and the coefficient to obtain the processing result of the single emission received signal; finally, processing the processing result of each transmitting and receiving signal by using the generalized coherent coefficient again; the method is obviously superior to the traditional time delay superposition and synthesis focusing imaging method in improving the image resolution, the contrast and correcting the focusing error.
Description
Technical Field
The invention relates to the technical field of ultrasonic imaging, in particular to a synthetic focus imaging method based on a generalized coherence coefficient.
Background
Synthetic aperture focused ultrasound imaging is a relatively promising imaging method developed in the 70's of the 20 th century. Unlike conventional time-delay superposition methods (DAS), synthetic aperture focus imaging can achieve better resolution with a lower operating frequency and smaller transducer aperture. With the development of the research, a series of improved synthetic aperture imaging techniques are proposed in succession, such as multi-element synthetic aperture focusing, synthetic receive aperture, synthetic transmit aperture. Both of these methods are effective in improving the quality of beam forming to some extent. Among them, the beam formed by the Synthetic Focus (SF) has the highest quality, and the effect is the best regardless of the width of the slave main lobe or the suppression of the side lobe. However, in actual ultrasonic imaging, the acoustic impedance difference of the detected object causes the sound velocity to be uneven, so that focusing errors are inevitable; according to the reports of relevant documents, certain difference exists in sound velocity in different types of human soft tissues. Even within the same type of soft tissue, there is a difference in sound velocity due to tissue inhomogeneity. Phase distortion caused by acoustic velocity non-uniformity is an important source leading to degradation of ultrasound imaging quality. Therefore, how to reduce the decrease of the ultrasonic imaging resolution and contrast due to the sound velocity unevenness is a hot research focus in recent years. Donnell et al propose a phase delay estimation method of phase correction, which effectively solves the problems of poor focusing characteristics and imaging quality caused by phase distortion due to sound velocity nonuniformity.
Therefore, a synthetic focusing imaging method which is obviously superior to the traditional delay superposition in the aspects of improving the image resolution and the contrast and correcting the focusing error is urgently needed.
Disclosure of Invention
In view of the above, in order to solve the above problems, the present invention provides a synthetic focus imaging method that is significantly better than the conventional time-delay superposition in image resolution, contrast, and focus error correction.
The invention aims to provide a synthetic focusing imaging method based on a generalized coherence coefficient;
the purpose of the invention is realized as follows:
the invention provides a synthesis focusing imaging method based on a generalized coherence coefficient, which comprises the following steps:
s1: obtaining data signal S of K point in space, transmitted by ith transmitting array element and received by M receiving array elementsi(k)，
Wherein S isi(k)＝[si，1(k)，…，si，M(k)]，si，j(k) Indicating the transmission of the ith transmitting array elementThe data signal received by the Mth receiving array element;
s2: calculating a data signal Si(k) First generalized coherence coefficient ω1；
S3: the data signal Si(k) After summation, the sum is combined with a first generalized coherence coefficient omega1Weighting to obtain a single processed signal y of the ith transmitting and receiving signali(k) I.e. the i-th transmitted processed signal y is calculated by the following formulai(k)；
Wherein S isi，j(k) The data signals transmitted by the ith transmitting array element and received by the jth receiving array element are represented, and M represents the number of the receiving array elements;
s4: repeating S1-S3 to calculate the processing signal Y of all the transmitting array elementsi(k) The processing signal is:
Yi(k)＝[y1(k)，y2(k)，...yN(k)]wherein, yN(k) A processed signal representing a single nth time transmission unit;
s5: calculating the processing signal Y of all transmitting array elementsi(k) Second generalized coherence coefficient ω2；
S6: processing signals Y of all transmitting array elementsi(k) After summation, the sum is combined with a second generalized coherence coefficient omega2Weighting to obtain the amplitude of the K-th point in space,wherein p (K) represents the image amplitude at the K-th point in space;
s7: repeating S1-S6 traverses the image data signals for all points in space.
Further, the data signal S in S1i(k) Transmitting an ith transmitting array element and receiving echo signals related to a K point in space through M receiving array elements to form data signals through focusing delay processing;
further, the first generalized coherence coefficient ω in S21The calculation specifically comprises the following steps:
s21: for data signal Si(k) Forming beam domain data by performing a discrete Fourier transform with the following formula
Where M denotes the number of receiving array elements, M-0 to M-1 denotes the spatial frequency coefficient, si，j(k) Representing the data signal transmitted by the ith transmit array element, received by the jth receive array element, d representing the array element spacing,representing data transmitted by the ith transmitting array element and converted to a beam domain through data received by the M receiving array elements;
S22： <math>
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wherein, GCF1(n) represents a first-order generalized coherence coefficient ω1N is a control GCF1(n) energy ratio of low-frequency components.
Further, m in the step S22 is 0, and the first generalized coherence coefficient is calculated by the following formula:
wherein,
the frequency spectrum of the 0 th point in the data which is transmitted by the ith transmitting array element and is converted into the beam domain through the data received by the M receiving array elements is represented;
further, the processing signals Y of all the transmitting array elements in S5i(k) Second generalized coherence coefficient ω2The calculation specifically comprises the following steps:
s51: for the processing signal Yi(k) Discrete Fourier transform beamforming of beam domain data by the following formula
Wherein M represents the number of transmitting array elements, yi(k) Representing the processed signal of the ith transmitting array element, M-0 to M-1 representing space frequency coefficient, d representing the distance between array elements, and the beam domain data
And the processed signals representing all M transmitting array elements are transformed into the data of the beam domain.
S52: the second-order generalized coherence coefficient is calculated by the following formula:
wherein, GCF2(n) represents the second-order generalized coherence coefficient ω2N is a control GCF2(n) energy ratio of low-frequency components.
Further, m in the step S52 is 0, and the second generalized coherence coefficient is calculated by the following formula:
wherein,
and the frequency spectrum of the 0 th point in the data after all the processing signals of the M transmitting array elements are transformed into the beam domain. The invention has the advantages that: the method utilizes the robustness of the generalized coherence coefficient when the phase has errors and the characteristic of high resolution of synthetic focus imaging, introduces the generalized coherence coefficient into the synthetic focus imaging method, and uses the generalized coherence coefficient as a self-adaptive weighting factor to correct the focus error caused by sound velocity nonuniformity; the method improves the resolution ratio, corrects the focusing error introduced by the sound velocity nonuniformity of the biological tissue, and carries out double generalized coherence coefficient algorithm processing on echo data aiming at the characteristic of synthetic focusing data.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of a generalized coherence coefficient based synthetic focus imaging method;
FIG. 2 is a spatial geometry of the transmit and receive of a synthetic focused beam;
FIG. 3 is a graph of various imaging contrasts of a point target;
FIG. 4 is a cross-resolution contrast plot of a point target at a depth of 60 mm;
FIG. 5 is a graph of various imaging contrasts of a point target;
FIG. 6 is a lateral resolution of the spot target at 60mm for various imaging methods.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings; it should be understood that the preferred embodiments are illustrative of the invention only and are not limiting upon the scope of the invention.
The invention introduces the generalized coherence coefficient into the synthetic focusing imaging method by utilizing the robustness of the generalized coherence coefficient when the phase has errors and the characteristic of high resolution of synthetic focusing imaging, wherein the basic principle of synthetic focusing is as follows: assuming that the total number of array elements is M, the first time is the 1 st array element transmission and full aperture receiving; the second time is the 2 nd array element transmission and full aperture receiving; and the rest is repeated until the last array element is transmitted at the Mth time, and the full aperture is received. The resulting data set of the synthetic focus contains the combined relationship of all single array element transmissions and all array element receptions. As shown in fig. 2, fig. 2 shows the spatial geometrical relationship of transmit and receive of the synthesized focused beam, and for a certain point K in space, the synthesized focus is expressed as:
in the formula, Si(r, theta) represents the synthesized focused signal, Sm，n(t) is the received echo signal, M is the total number of transmitting and receiving elements, τnFor the transmission delay time of the nth transmitting array element, taumThe receiving delay time of the mth receiving array element is represented by r, the distance from a point K to a coordinate origin in space is represented by theta, the included angle between a connecting line of the point K and the coordinate origin in space and a central line is represented by theta, r/c is the time of the linear array ultrasonic signal from a certain point K (x, y) in space to the coordinate origin, and omega is the time of the linear array ultrasonic signal propagating from the certain point K (x, y) in space to the coordinate origin1、ω2The parameters are weighted for complex values.
FIG. 1 is a flow chart of a generalized coherence coefficient-based synthetic focus imaging method, as shown in the figure: the invention provides a synthesis focusing imaging method based on a generalized coherence coefficient, which comprises the following steps:
firstly, initializing parameters in a program, including setting initial values of a K-th point in space, a transmitting array element and a receiving array element;
s1: obtaining data signal S of K point in space, transmitted by ith transmitting array element and received by M receiving array elementsi(k) Wherein S isi(k)＝[si，1(k)，…，si，M(k)]，si，M(k) The data signal received by the Mth receiving array element is transmitted by the ith transmitting array element;
the data signal S in S1i(k) The data signal is formed by focusing and delaying a receiving echo signal which is transmitted by the ith transmitting array element and received by the M receiving array elements and is related to the K point in space. Because the distances from the echo signals of the intermediate point targets to each array element are different and the time from the echo signals to each channel is different, the delay time from each channel is calculated according to the parameters of the transducer and delayed so as to achieve in-phase addition.
S2: calculating a data signal Si(k) First generalized coherence coefficient ω1(ii) a The first generalized coherence coefficient ω1The calculation specifically comprises the following steps:
s21: : for data signal Si(k) Forming beam domain data by performing a discrete Fourier transform with the following formula
Where M denotes the number of receiving array elements, M-0 to M-1 denotes the spatial frequency coefficient, si，j(k) Representing the data signal transmitted by the ith transmit array element, received by the jth receive array element, d representing the array element spacing,
representing data transmitted by the ith transmit array element and received by the M receive array elements after transformation to the beam domain.
S22: the first-time generalized coherence coefficient is calculated by the following formula:
wherein, GCF1(n) represents a first-order generalized coherence coefficient ω1N is a control GCF1(n) energy ratio of low-frequency components.
Among them, according to Parseval's theorem,
the value of m in step S22 is 0, and the first generalized coherence coefficient is calculated by the following formula:
wherein,
representing the spectrum of the 0 th point in the data transmitted by the ith transmitting array element and received by the M receiving array elements after transformation to the beam domain.
S3: the data signal Si(k) After summation, the sum is combined with a first generalized coherence coefficient omega1Weighting to obtain a single processed signal y of the ith transmitting and receiving signali(k) I.e. the i-th transmitted processed signal y is calculated by the following formulai(k)；
Wherein S isi，j(k) The ith transmitting array element transmits a data signal received by the jth receiving array element, and M represents the number of the receiving array elements;
s4: repeating S1-S3 to calculate the processing signal Y of all the transmitting array elementsi(k) Processing the processing signal of the next transmitting array element until the processing signals of all transmitting array elements are processed, wherein the processing signals are as follows:
Yi(k)＝[y1(k)，y2(k)，...yN(k)]wherein, yN(k) A processed signal representing a single nth time transmission unit;
s5: calculating the processing signal Y of all transmitting array elementsi(k) Second generalized coherence coefficient ω2The second generalized coherence coefficient ω2The calculation specifically comprises the following steps:
s51: for the processing signal Yi(k) Discrete Fourier transform beamforming of beam domain data by the following formula
Wherein M represents the number of transmitting array elements, yi(k) Representing the processed signal of the ith transmitting array element, M-0 to M-1 representing space frequency coefficient, d representing the distance between array elements, and the beam domain data
And the processed signals representing all M transmitting array elements are transformed into the data of the beam domain.
S52: the second-order generalized coherence coefficient is calculated by the following formula:
wherein, GCF2(n) represents the second-order generalized coherence coefficient ω2N is a control GCF2(n) energy ratio of low-frequency components.
Among them, according to Parseval's theorem,
the value of m in step S52 is 0, and the second-time generalized coherence coefficient is calculated by the following formula:
wherein,
and the frequency spectrum of the 0 th point in the data after all the processing signals of the M transmitting array elements are transformed into the beam domain. S6: processing signals Y of all transmitting array elementsi(k) After summation, the sum is combined with a second generalized coherence coefficient omega2Weighting to obtain the amplitude of the K-th point in space,
wherein p (K) represents the image amplitude at the K-th point in space;
s7: repeating S1-S6 traverses the image data signals for all points in space. And processing the image data signals of the next spatial point until the image data signals of all spatial points are processed.
The simulation of Synthetic Focus (SF) using the Field II ultrasound simulation software to generate a complete simulation data set to complete a series of comparison tests is described in detail below.
The simulation parameters are set as follows: the array comprises 64 array elements and is characterized in that the center frequency of the linear array is 3.5MHz, the sound velocity is 1540m/s, the array element interval is half wavelength, and the sampling frequency is 50 MHz. The 9 scattering point spatial targets (x, y, z) are (0, 0, 30), (0, 0, 40), (-4, 0, 50), (-2, 0, 50), (0, 0, 50), (2, 0, 50), (4, 0, 50), (0, 0, 60), (0, 0, 70).
FIG. 3 is a diagram of various imaging contrasts of a point target, and FIG. 4 is a diagram of a transverse resolution contrast of the point target at a depth of 60 mm; FIG. 5 is a graph of various imaging contrasts of a point target; FIG. 6 shows the lateral resolution of the various imaging methods of the point target at 60mm, and as shown, FIG. 3 shows the results of the different methods for imaging scattering points of different depths, where (a) represents the conventional time-delay overlay (DAS); (b) denotes Synthetic Focus (SF); (c) represents the combined focus and coherence coefficient (SF + CF); (d) representing the combined focus and generalized coherence coefficient, with the band parameter m equal to 1(SF + GCF)1)。
As can be derived from fig. 3, the resolution and contrast obtained in fig. 3(b) are significantly higher than in fig. 3(a), since synthetic focusing enables bi-directional focusing of transmit and receive, enabling better resolution and contrast to be obtained relative to DAS; the synthetic focusing algorithm is combined with CF and GCF, and the resolution and contrast of the image are obviously improved. Wherein, the image effect is improved more obviously by combining with the CF algorithm. This is because for the case of point targets and phase error-free, the generalized coherence coefficient numerator adds redundant summation terms, so that the algorithm is close to the unweighted direction, and thus the imaging quality of fig. 3(d) is slightly degraded compared with that of fig. 3 (c).
In order to further study the situation of resolution and contrast, a cross section was taken for observation. Fig. 4 gives a transverse resolution contrast at a depth of 60 mm. It can be seen from fig. 4 that the SF and CF combination method gives the highest resolution and contrast, followed by the SF and GCF combination method, and finally followed by SF and DAS.
Studies according to the relevant literature show that: the imaging quality cannot be comprehensively evaluated only by analyzing the point scattering targets. The GCF algorithm is proposed in the case that each echo signal has incoherent characteristics, and if only the coherence coefficient weighting is used, the best imaging effect cannot be obtained without considering the influence. Therefore, a simulated imaging experiment is next performed for the plaque scattering target.
The imaging depth of the spot scattering target is 30-50 mm. The scattering target is a circular sound absorber with a radius of 5mm and a center at a depth of 40mm, and the scatterers are in Gaussian distribution. The simulation parameter setting is consistent with the point scattering target simulation parameter. FIG. 5 is a reconstructed image of different beamforming methods, wherein (a) represents a conventional time delay overlay (DAS); (b) denotes Synthetic Focus (SF); (c) represents the combined focus and coherence coefficient (SF + CF); (d) representing the combined focus and generalized coherence coefficient, the band parameter m is 1(SF + GCF 1).
As can be seen from fig. 5, the outline of the outer background region in fig. 5(b) is more clear than that of fig. 5 (a); SF, when combined with CF or GCF, respectively, the image contrast of fig. 5(c) and 5(d) is significantly improved, while the central circular acoustic absorber is more sharply outlined with no artifacts. The intensity of the background area varies greatly after weighting with CF. This is because for a speckle scattering target, the low frequency range for the estimation of the GCF should be extended due to the inherent incoherence of the received signals of the channels.
To further demonstrate that the GCF can still obtain good imaging effect when there is focus error. The imaging experiment of the point object was repeated and the image was reconstructed with an incorrect speed of sound (1570 m/s). FIG. 6 shows a comparison of the lateral resolution of various imaging methods of a point target at a depth of 60 mm.
As can be seen from fig. 6, due to the focusing error, the improvement of the image quality by the synthesized focusing is not obvious compared with the conventional delay superposition algorithm, but the image side lobe level is suppressed and the image contrast is improved after the CF and GCF are used for weighting.
In summary, the embodiments provided by the present invention provide an imaging method that introduces a generalized coherence coefficient into a synthetic focus for solving the problems of insufficient resolution of an actual medical ultrasound image and a focus error caused by non-uniformity of biological tissues, and fully utilize the characteristic of high resolution of the synthetic focus and the generalized coherence coefficient as an adaptive weighting factor to correct the focus error caused by non-uniformity of sound velocity.
According to the imaging experiment results of the point scattering target and the spot scattering target, the following results can be obtained: the method can effectively improve the resolution and the contrast of the image; even if a focusing error exists, a better imaging effect can be obtained by effectively inhibiting the side lobe; considering that the point scattering target and the spot scattering target have different characteristics, the low-frequency parameter range settings of the molecular parts in the generalized coherence coefficient parameter are also different. According to a large number of experimental tests, it is shown that: for point targets, m is typically chosen to be 0, i.e. weighted with a coherence coefficient; for the spot scattering point, m is generally selected to be 1-3 in consideration of the inherent coherence of the received signal.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and it is apparent that those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (6)
1. The synthetic focusing imaging method based on the generalized coherence coefficient is characterized in that: the method comprises the following steps:
s1: obtaining data signal S of K point in space, transmitted by ith transmitting array element and received by M receiving array elementsi(k) Wherein S isi(k)＝[si，1(k)，…，Si，M(k)]，si，M(k) The data signal received by the Mth receiving array element is transmitted by the ith transmitting array element;
s2: calculating a data signal Si(k) First generalized coherence coefficient ω1；
S3: the data signal Si(k) After summation, the sum is combined with a first generalized coherence coefficient omega1Weighting to obtain a single processed signal y of the ith transmitting and receiving signali(k) I.e. the i-th transmitted processed signal y is calculated by the following formulai(k)；
Wherein s isi，j(k) The data signals transmitted by the ith transmitting array element and received by the jth receiving array element are represented, and M represents the number of the receiving array elements;
s4: repeating S1-S3 to calculate the processing signal Y of all the transmitting array elementsi(k) The processing signal is:
Yi(k)＝[y1(k)，y2(k)，...yN(k)]wherein, yN(k) A processed signal representing a single nth time transmission unit;
s5: calculating the processing signal Y of all transmitting array elementsi(k) Second generalized coherence coefficient ω2；
S6: processing signals Y of all transmitting array elementsi(k) After summation, the sum is combined with a second generalized coherence coefficient omega2Weighting to obtain the amplitude of the K-th point in space,
wherein p (K) represents the image amplitude at the K-th point in space;
s7: repeating S1-S6 traverses the image data signals for all points in space.
2. A method of synthetic focus imaging based on generalized coherence coefficients according to claim 1, characterized by: the data signal S in S1i(k) The data signal is formed by focusing and delaying the reception echo signal of the Kth point of the space which is transmitted by the ith transmitting array element and received by the M receiving array elements.
3. A method of synthetic focus imaging based on generalized coherence coefficients according to claim 2, characterized by: the first generalized coherence coefficient ω in S21The calculation specifically comprises the following steps:
s21: for data signal Si(k) Forming beam domain data by performing a discrete Fourier transform with the following formula
Where M denotes the number of receiving array elements, M-0 to M-1 denotes the spatial frequency coefficient, si，j(k) Representing the data signal transmitted by the ith transmit array element, received by the jth receive array element, d representing the array element spacing,
representing data transmitted by the ith transmitting array element and converted to a beam domain through data received by the M receiving array elements;
s22: the first-time generalized coherence coefficient is calculated by the following formula:
wherein, GCF1(n) represents a first-order generalized coherence coefficient ω1N is a control GCF1(n) energy ratio of low-frequency components.
4. A method of synthetic focus imaging based on generalized coherence coefficients according to claim 3, characterized by: the value of m in step S22 is 0, and the first generalized coherence coefficient is calculated by the following formula:
wherein,
representing the spectrum of the 0 th point in the data transmitted by the ith transmitting array element and received by the M receiving array elements after transformation to the beam domain.
5. The method of claim 4, wherein: processing signals Y of all transmitting array elements in S5i(k) Second generalized coherence coefficient ω2The calculation specifically comprises the following steps:
s51: for the processing signal Yi(k) Discrete Fourier transform beamforming of beam domain data by the following formula
Wherein M represents the number of transmitting array elements, yi(k) Representing the processed signal of the ith transmitting array element, M-0 to M-1 representing space frequency coefficient, d representing the distance between array elements, and the beam domain data
Data which represents the processed signals of all M transmitting array elements and is transformed into a beam domain;
s52: the second-order generalized coherence coefficient is calculated by the following formula:
wherein, GCF2(n) represents the second-order generalized coherence coefficient ω2N is a control GCF2(n) energy ratio of low frequency components.
6. The method of claim 5, wherein: the value of m in step S52 is 0, and the second-time generalized coherence coefficient is calculated by the following formula:
wherein,
and the frequency spectrum of the 0 th point in the data after all the processing signals of the M transmitting array elements are transformed into the beam domain.
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| CN102920478A (en) * | 2012-11-22 | 2013-02-13 | 山东大学 | Synthetic-focusing imaging method of portable type-B ultrasonic equipment |
| CN103033816A (en) * | 2012-12-07 | 2013-04-10 | 清华大学 | Synthetic aperture focused ultrasonic imaging implementation method based on arc scanning transition |
| CN103565469A (en) * | 2012-08-01 | 2014-02-12 | 华中科技大学 | Method for improving two-dimensional array real-time ultrasonic body imaging quality |
| CN103969651A (en) * | 2014-04-24 | 2014-08-06 | 中国科学院声学研究所 | Self-adaptive acoustic imaging method |
| CN105319543A (en) * | 2015-06-26 | 2016-02-10 | 中国科学院声学研究所 | Wave beam forming method based on constant horizontal resolution |
| WO2016155239A1 (en) * | 2015-03-27 | 2016-10-06 | 清华大学 | Method and device for ultrasonic imaging by synthetic focusing |
| CN108618799A (en) * | 2018-04-24 | 2018-10-09 | 华中科技大学 | A kind of ultrasonic CT imaging process based on spatial coherence |
| CN110507355A (en) * | 2019-09-20 | 2019-11-29 | 青岛海信医疗设备股份有限公司 | A kind of ultrasonic image-forming system, method, equipment and medium |
| CN111856474A (en) * | 2020-07-30 | 2020-10-30 | 重庆大学 | A Subarray-Based Conditional Coherence Coefficient Ultrasound Imaging Method in Space-Time Domain |
| CN113625286A (en) * | 2021-08-03 | 2021-11-09 | 重庆大学 | Strong Robust Truncated Coherence Coefficient Ultrasonic Beamforming Based on Coherent Features |
| CN113647978A (en) * | 2021-08-18 | 2021-11-16 | 重庆大学 | High-robustness symbol coherence coefficient ultrasonic imaging method with truncation factor |
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| CN103565469A (en) * | 2012-08-01 | 2014-02-12 | 华中科技大学 | Method for improving two-dimensional array real-time ultrasonic body imaging quality |
| CN103565469B (en) * | 2012-08-01 | 2015-05-20 | 华中科技大学 | Method for improving two-dimensional array real-time ultrasonic body imaging quality |
| CN102920478A (en) * | 2012-11-22 | 2013-02-13 | 山东大学 | Synthetic-focusing imaging method of portable type-B ultrasonic equipment |
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| CN103969651A (en) * | 2014-04-24 | 2014-08-06 | 中国科学院声学研究所 | Self-adaptive acoustic imaging method |
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| CN108618799A (en) * | 2018-04-24 | 2018-10-09 | 华中科技大学 | A kind of ultrasonic CT imaging process based on spatial coherence |
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| CN110507355A (en) * | 2019-09-20 | 2019-11-29 | 青岛海信医疗设备股份有限公司 | A kind of ultrasonic image-forming system, method, equipment and medium |
| CN111856474A (en) * | 2020-07-30 | 2020-10-30 | 重庆大学 | A Subarray-Based Conditional Coherence Coefficient Ultrasound Imaging Method in Space-Time Domain |
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| CN113625286A (en) * | 2021-08-03 | 2021-11-09 | 重庆大学 | Strong Robust Truncated Coherence Coefficient Ultrasonic Beamforming Based on Coherent Features |
| CN113625286B (en) * | 2021-08-03 | 2023-11-14 | 重庆大学 | Strong robustness truncated coherence coefficient ultrasonic beam forming method based on coherence features |
| CN113647978A (en) * | 2021-08-18 | 2021-11-16 | 重庆大学 | High-robustness symbol coherence coefficient ultrasonic imaging method with truncation factor |
| CN113647978B (en) * | 2021-08-18 | 2023-11-21 | 重庆大学 | High-robustness symbol coherence coefficient ultrasonic imaging method with truncation factor |
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