Ultrasonic volume data rendering imaging method, device and storage medium

Abstract

The present invention relates to an ultrasonic volume data rendering imaging method, device and storage medium, the method comprising: obtaining original data of three-dimensional volume data; interpolating and reconstructing the original data of the three-dimensional volume data to obtain voxels corresponding to the three-dimensional volume data and transparency parameters corresponding to the voxels; obtaining a two-dimensional rendering of the three-dimensional volume data according to the voxels and transparency parameters; extracting the light and dark attenuation coefficients of the contour of the tissue structure under the same light beam in the three-dimensional volume data according to the voxels and transparency parameters, and obtaining a contour structure rendering of the three-dimensional volume data according to the light and dark attenuation coefficients of the contour of the tissue structure; fusing the two-dimensional rendering of the three-dimensional volume data with the contour structure rendering to obtain the desired image and display it. The present invention strengthens the structural relationship between tissues, highlights the contours of the tissues, makes the overall effect of the fused image more realistic, and achieves the purpose of optimizing rendering imaging.

Description

Technical Field

[0001] The present invention relates to the field of medical technology, and in particular to an ultrasonic volume data rendering imaging method, device and storage medium. Background Art

[0002] Three-dimensional ultrasound diagnostic technology was rapidly introduced to the clinic in the late 1990s. Its unique three-dimensional imaging function has played an increasingly important role in obstetric fetal examinations in recent years. Compared with two-dimensional ultrasound imaging, three-dimensional ultrasound imaging technology not only has all its functions and advantages, but also has functions that two-dimensional ultrasound imaging cannot achieve, such as examining changes in the placenta, amniotic fluid and umbilical cord. Compared with traditional two-dimensional ultrasound technology, three-dimensional ultrasound imaging has obvious advantages in the diagnosis of fetal facial deformities, gallbladder blood vessels, small organs and bladder and other fluid-containing organs.

[0003] Among the existing ultrasound imaging technologies, 3D ultrasound imaging is to display the 3D ultrasound image of the tissue being measured by collecting 3D volume data and rendering the volume data. Usually, the 3D ultrasound imaging system also supports the interactive operation of 3D view and cross-sectional view, including translation, rotation, scaling, switching cross-sectional view, adjusting the cross-sectional view position, etc. After the above series of operations, the 3D stereogram and cross-sectional image are obtained to help the ultrasound doctor's diagnosis. The effect diagram is as follows Figure 2 shown.

[0004] However, when ultrasound doctors use three-dimensional stereograms for diagnosis, whether rendering the three-dimensional ultrasound image or rendering each object or area, current medical ultrasound instruments usually use the same rendering. The rendered image is positively correlated with the atlas, the image effect is not smooth and gentle, and the image style is hard. The problem with this display method is that when multiple objects overlap in a certain visual sense, it is not easy to highlight this tissue feature in the three-dimensional image.

[0005] Therefore, the tissue image information obtained by the current ultrasound three-dimensional rendering mode is relatively rigid and cannot highlight the structural contours, resulting in the user being unable to clearly and intuitively diagnose the tissue through the three-dimensional image. Summary of the invention

[0006] In view of this, it is necessary to provide an ultrasound volume data rendering imaging method, device and storage medium to solve the problem that tissue contours cannot be highlighted during current ultrasound three-dimensional rendering.

[0007] The present invention provides an ultrasound volume data rendering imaging method, comprising the following steps:

[0008] Acquire raw data of three-dimensional volume data;

[0009] Interpolating and reconstructing the original data of the three-dimensional volume data to obtain voxels corresponding to the three-dimensional volume data and transparency parameters corresponding to the voxels;

[0010] Acquire a two-dimensional rendering of the three-dimensional volume data according to the voxel and the transparency parameter;

[0011] Extracting the bright and dark attenuation coefficient of the tissue structure contour under the same light beam in the three-dimensional volume data according to the voxel and transparency parameter, and obtaining a contour structure rendering image of the three-dimensional volume data according to the bright and dark attenuation coefficient of the tissue structure contour;

[0012] The two-dimensional rendering of the three-dimensional volume data is merged with the contour structure rendering to obtain the required image and display it.

[0013] Preferably, in the ultrasound volume data rendering imaging method, the step of extracting the light and dark attenuation coefficient of the tissue structure contour under the same light in the three-dimensional volume data according to the voxel and transparency parameter, and obtaining the contour structure rendering image of the three-dimensional volume data according to the light and dark attenuation coefficient of the tissue structure contour specifically includes:

[0014] Determine the number n1 of points that pass through the three-dimensional volume data under a light beam, wherein the n1 points are all points whose voxels are greater than a preset voxel threshold;

[0015] Counting the average transparency of n2 points around each of the n1 points selected, and determining the light attenuation coefficient of each of the n1 points according to the average transparency;

[0016] According to the transparency of each point in the n1 points, weighted accumulation is performed on the light attenuation coefficients of the n1 points to obtain the bright and dark attenuation coefficients on the light beam;

[0017] The bright and dark attenuation coefficients on the light beam are optimized to obtain the final bright and dark attenuation coefficients of the tissue structure contour, and then the bright and dark attenuation coefficients of the tissue structure contour are normalized;

[0018] The normalized tissue structure contour light and dark attenuation coefficients are color mapped to obtain a contour structure rendering of the three-dimensional volume data.

[0019] Preferably, in the ultrasound volume data rendering imaging method, the preset voxel threshold is 0.02, the preset transparency accumulation threshold is 0.95, and the preset sampling depth threshold is 150.

[0020] Preferably, in the ultrasound volume data rendering imaging method, the calculation formula for the mean transparency of n2 points is:

[0021]

[0022] Among them, at n is the average transparency of n2 points around the nth point among n1 points, aw i is the transparency of the i-th point among n2 points, where n2 is a natural number.

[0023] Preferably, in the ultrasound volume data rendering imaging method, the calculation formula for the light attenuation coefficient of each point in the n1 points is:

[0024] ak n =1-at n ,

[0025] Among them, at n is the average transparency of the n2 points around the nth point among the n1 points, ak n is the light attenuation coefficient of the nth point among n1 points, and the value of n ranges from 0 to n1.

[0026] Preferably, in the ultrasound volume data rendering imaging method, the calculation formula of the bright and dark attenuation coefficient on the light beam is:

[0027] ak1 n+1 =ak1 n +ak n *(1-sum.w n ),

[0028] Among them, ak1 n is the brightness attenuation coefficient before accumulation, ak1 n+1 is the accumulated brightness attenuation coefficient, ak n is the light attenuation coefficient of the nth point among n1 points, sum.w n It is the accumulated transparency value of n1 points.

[0029] Preferably, in the ultrasound volume data rendering imaging method, the calculation formula of the final tissue structure contour light and dark attenuation coefficient is:

[0030] ak2=fak(ak1)=a*ak1 m1 +b*ak1 m2 ,

[0031] Among them, ak2 is the final tissue structure contour brightness and darkness attenuation coefficient, ak1 is the light attenuation coefficient, and a, b, m1 and m2 are empirical parameters.

[0032] Preferably, in the ultrasound volume data rendering imaging method, the following formula is used to fuse the two-dimensional rendering image of the three-dimensional volume data with the contour structure rendering image:

[0033] P=a1*Pag+a2*Pam,

[0034] Among them, Pag is the two-dimensional rendering of the three-dimensional volume data, Pam is the contour structure rendering, P is the required image, and a1 and a2 are empirical constants.

[0035] In a second aspect, the present invention further provides an ultrasound volume data rendering imaging device, comprising: a processor and a memory;

[0036] The memory stores a computer-readable program executable by the processor;

[0037] When the processor executes the computer-readable program, the steps in the ultrasound volume data rendering imaging method as described above are implemented.

[0038] In a third aspect, the present invention further provides a computer-readable storage medium storing one or more programs, wherein the one or more programs can be executed by one or more processors to implement the steps in the ultrasound volume data rendering imaging method as described above.

[0039] Compared with the prior art, the ultrasound volume data rendering imaging method, device and storage medium provided by the present invention output the contour of the tissue in the three-dimensional volume data better, and the characteristic effect of the contour is more significant. In addition, by assigning different light intensities to the characteristic contours or mapping different spectra, the fused image effect can be made better. The system first obtains the structural parameters of the characteristic structure area, attenuates the uniform light intensity through the structural parameters, and fuses the display effect of the structure area with the effect of traditional three-dimensional ultrasound surface imaging to obtain a better rendering effect, so that users can diagnose tissues more clearly and intuitively through three-dimensional images, strengthen the structural relationship between tissues, highlight the structural contours, make the overall effect of the fused image more realistic, and achieve the purpose of optimizing rendering imaging. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A flowchart of a preferred embodiment of the ultrasound volume data rendering imaging method provided by the present invention;

[0041] Figure 2 Rendering effect diagram for traditional ultrasound 3D volume data;

[0042] Figure 3 A schematic diagram of a first specific embodiment of a rendering diagram of a contour structure of three-dimensional volume data according to the present invention;

[0043] Figure 4 A schematic diagram of a second specific embodiment of a rendering diagram of a contour structure of three-dimensional volume data according to the present invention;

[0044] Figure 5 It is a schematic diagram of a first specific embodiment of an ultrasound volume data rendering effect diagram of the present invention;

[0045] Figure 6 It is a schematic diagram of a second specific embodiment of an ultrasound volume data rendering effect diagram of the present invention. DETAILED DESCRIPTION

[0046] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0047] See also Figure 1 The ultrasound volume data rendering imaging method provided by the embodiment of the present invention comprises the following steps:

[0048] S100: Acquire original data of three-dimensional volume data.

[0049] In this embodiment, the ultrasonic probe is controlled to collect multiple continuous two-dimensional B-ultrasound images as raw data of three-dimensional volume data, wherein the raw data format of the three-dimensional volume data is B-ultrasound data. In a specific embodiment, it is assumed that the collected volume data is 51 frames of 384*800, wherein 384 is the lateral resolution and 800 is the axial resolution. The imaging depth is 140 mm, the scanning angle is 60, the scanning radius of the probe is 39.71 mm, and the swing radius of the probe is 17.79 mm.

[0050] S200 , performing interpolation reconstruction on original data of the three-dimensional volume data to obtain voxels corresponding to the three-dimensional volume data and transparency parameters corresponding to the voxels.

[0051] In this embodiment, after the original data of the three-dimensional volume data is obtained, the original data of the three-dimensional volume data is interpolated and reconstructed, and the reconstructed three-dimensional volume data is consistent with the spatial structure of the measured tissue. The corresponding voxel of the reconstructed three-dimensional volume data is ag, and a transparency parameter aw is assigned to each voxel. In a specific embodiment, the original data of 51*384*800 is converted into 600*600*400 volume data through interpolation reconstruction. In a preferred embodiment, ag and aw are both normalized to values ​​between 0 and 1.

[0052] S300: Acquire a two-dimensional rendering of the three-dimensional volume data according to the voxels and the transparency parameter.

[0053] In this embodiment, the reconstructed voxel ag is combined with aw and projected using plane light through a ray projection algorithm to obtain a two-dimensional rendering image Pag of the traditional three-dimensional volume data. The ray projection algorithm is a prior art and will not be described in detail here.

[0054] S400 , extracting the light and dark attenuation coefficients of the tissue structure contour under the same light beam in the three-dimensional volume data according to the voxels and transparency parameters, and obtaining a contour structure rendering of the three-dimensional volume data according to the light and dark attenuation coefficients of the tissue structure contour.

[0055] In this embodiment, in order to better output the tissue contour in the three-dimensional volume data and make the characteristic effect of the contour more significant, different light intensities are given to the characteristic contours or different spectra are mapped, so as to make the fused image effect better. In the specific implementation, the structural parameters of the characteristic structure area are first obtained, and the same light intensity is attenuated by the structural parameters, and the display effect of the structure area is fused with the effect of traditional three-dimensional ultrasonic surface imaging to obtain a better rendering effect. Specifically, the step S400 specifically includes:

[0056] Determine the number n1 of points that pass through the three-dimensional volume data under a light beam, wherein the n1 points are all points whose voxels are greater than a preset voxel threshold;

[0057] Counting the average transparency of n2 points around each of the n1 points selected, and determining the light attenuation coefficient of each of the n1 points according to the average transparency;

[0058] According to the transparency of each point in the n1 points, weighted accumulation is performed on the light attenuation coefficients of the n1 points to obtain the bright and dark attenuation coefficients on the light beam;

[0059] The bright and dark attenuation coefficients on the light beam are optimized to obtain the final bright and dark attenuation coefficients of the tissue structure contour, and then the bright and dark attenuation coefficients of the tissue structure contour are normalized;

[0060] The normalized tissue structure contour light and dark attenuation coefficients are color mapped to obtain a contour structure rendering of the three-dimensional volume data.

[0061] In this embodiment, the structural contour module of the ultrasound volume data is first obtained, and the volume data is subjected to a threshold limit nthread, and the structural brightness coefficient ak is extracted for each volume data within the threshold range, wherein the structural brightness coefficient ak of each volume data is a parameter less than 1 obtained by statistically normalizing the volume data pixels in the surrounding area of ​​the volume data and the associated color transparency aw. Then, the structural brightness coefficient on each plane light beam is accumulated in combination with the transparency, and finally the structural brightness coefficient ak1 of the light projection point is obtained, and the brightness optimization function fak(ak1) is processed on ak1 to obtain the ak2 coefficient with more significant attenuation. Finally, by color mapping the ak2 coefficient, a fixed color value is attenuated or mapped to a color spectrum of 0-1, and the color spectrum is designed by experience. Finally, the contour structure diagram of the volume data is obtained.

[0062] In a preferred embodiment, the preset voxel threshold is set to 0.02, and the structural bright and dark attenuation coefficient is extracted for volume data exceeding 0.02.

[0063] In a further embodiment, when determining the value of n1, it is determined by the beam downsampling spacing and the voxel transparency, that is, the value of n1 is affected by the transparency aw and the final sampling depth limit of the beam. Regarding the sampling degree limit, the transparency of the n1 voxels is weighted multiplied and accumulated, and the specific formula is as follows:

[0064] sum.w n+1 =sum.w n +(1-aw n ) (Formula 1)

[0065] In formula 1, aw n With sum.w n The transparency of the current voxel and the cumulative voxel transparency contribution, sum.w n+1 is the cumulative contribution value of transparency after accumulation. In this embodiment, wThread is taken as the cumulative transparency threshold, and wThread=0.95 is taken here. n+1 When the accumulation exceeds 0.95, the accumulation on this line is terminated, and n1 is determined. There is also a state sum.w n+1 The cumulative value cannot exceed 0.95. In view of this state, another restriction condition is set in this embodiment, that is, when sampling under this line beam, the sampling depth and step length are fixed. When the sampling step accumulation exceeds the sampling depth, the sampling is ended, that is, n1 is determined. The specific formula is as follows:

[0066] distance n+1 =distance n +stepSize (Formula 2)

[0067] In Formula 2, stepSize is a constant value, which is 0.4 in this embodiment, and the fixed length of the sampling depth is 150. If the sampling is terminated by the sampling depth, the corresponding n1 is 375.

[0068] Furthermore, the number of n2 can be adjusted appropriately to meet the calculation speed. The value of n2 takes the sampling point as the center of the sphere, takes Radius = 10 as the radius, and evenly takes 72*5*5 sampling points in the sphere. Of course, it should be understood that the value of n2 is not limited to the constant 72*5*5.

[0069] In a further embodiment, the calculation formula for the mean transparency of n2 points is:

[0070]

[0071] Among them, at n is the average transparency of n2 points around the nth point among n1 points, aw i is the transparency of the i-th point among n2 points, where n2 is a natural number.

[0072] Furthermore, when calculating the light attenuation coefficient of each of the n1 points, the following formula is used:

[0073] ak n =1-at n , (Formula 4)

[0074] Among them, at n is the average transparency of the n2 points around the nth point among the n1 points, ak n is the light attenuation coefficient of the nth point among n1 points, and the value of n ranges from 0 to n1.

[0075] After obtaining the light attenuation coefficient of each point among n1 points, the ak of n1 points is weightedly accumulated by the transparency aw of n1 points to obtain the light and dark attenuation coefficient ak1 on this beam. Specifically, the calculation formula of the light and dark attenuation coefficient on the beam is:

[0076] ak1 n+1 =ak1 n +ak n *(1-sum.w n ), (Formula 5)

[0077] Among them, ak1 n is the brightness attenuation coefficient before accumulation, ak1 n+1 is the accumulated brightness attenuation coefficient, ak n is the light attenuation coefficient of the nth point among n1 points, sum.w n It is the accumulated transparency value of n1 points.

[0078] After ak1 is obtained, the final tissue structure contour brightness and darkness attenuation coefficient ak2 is obtained using the brightness and darkness optimization function fak(ak1), and ak2 is normalized to between 0 and 1. Specifically, the calculation formula of the final tissue structure contour brightness and darkness attenuation coefficient is:

[0079] ak2=fak(ak1)=a*ak1 m1 +b*ak1 m2 , (Formula 6)

[0080] Among them, ak2 is the final tissue structure contour light and dark attenuation coefficient, ak1 is the light attenuation coefficient, a, b, m1 and m2 are empirical parameters, taking constant values. In this embodiment, a=0.7, b=0.3, m1=5, m2=2 are taken; since the value of ak1 is between 0-1, the value of ak2 is also between 0-1, and there is no need to normalize ak2 again here.

[0081] Finally, there are two ways to color map ak2. One is to give a certain light intensity and directly multiply the light intensity by ak2 to obtain the corresponding color value. The other is to map a spectrum between 0 and 1 and assign color values ​​to the corresponding ak2 beam points directly from the table through table interpolation. By using the above two methods to color map ak2, the contour structure rendering Pam is obtained. Figure 3 and Figure 4 In this example, the light intensity uses white light, the color format is RGB format, and the value is (255, 255, 255). The corresponding data format of the spectrum used is RGB*256.

[0082] S500: Fusing the two-dimensional rendering of the three-dimensional volume data with the contour structure rendering to obtain a desired image and display it.

[0083] In this embodiment, in order to obtain the final rendering, it is necessary to fuse the two-dimensional rendering obtained in step S300 and the contour structure rendering obtained in step S400 to finally obtain the desired image. Specifically, the two-dimensional rendering of the three-dimensional volume data and the contour structure rendering are fused using the following formula:

[0084] P=a1*Pag+a2*Pam, (Formula 7)

[0085] Wherein, Pag is a two-dimensional rendering of three-dimensional volume data, Pam is a contour structure rendering, P is a required image, a1 and a2 are empirical constants, and in this embodiment, a1=1, a2=1.

[0086] When the final desired image is obtained, it is displayed for human-computer interaction, such as Figure 5 and Figure 6 As shown, they are respectively the effect diagram after the fusion of traditional three-dimensional imaging and tissue structure contour (mapping atlas) and the effect diagram after the fusion of traditional three-dimensional imaging and tissue structure contour (fixed light intensity). It can be seen from the figure that the effect is obviously better and the tissue contour structure is more obvious.

[0087] It should be understood that although Figure 1The steps in the flowchart are shown in sequence according to the arrows, but these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be performed in other orders.

[0088] Based on the above ultrasound volume data rendering imaging method, the present invention also provides an ultrasound volume data rendering imaging device, including: a processor and a memory;

[0089] The memory stores a computer-readable program executable by the processor;

[0090] When the processor executes the computer-readable program, the steps in the ultrasound volume data rendering imaging method described in the above embodiments are implemented.

[0091] Since the ultrasound volume data rendering imaging method has been described in detail above, the technical effects of the ultrasound volume data rendering imaging method are also possessed by the ultrasound volume data rendering imaging device, and will not be described in detail here.

[0092] Based on the above-mentioned ultrasound volume data rendering imaging method, the present invention also provides a computer-readable storage medium accordingly, wherein the computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the ultrasound volume data rendering imaging method as described in the above-mentioned embodiments.

[0093] Since the ultrasound volume data rendering imaging method has been described in detail above, the technical effects of the ultrasound volume data rendering imaging method are also possessed by the ultrasound volume data rendering imaging device, and will not be described in detail here.

[0094] In summary, the ultrasound volume data rendering imaging method, device and storage medium provided by the present invention can output the contour of the tissue in the three-dimensional volume data better, and the characteristic effect of the contour is more significant. In addition, by assigning different light intensities to the characteristic contours or mapping different spectra, the fused image effect can be made better. The system first obtains the structural parameters of the characteristic structure area, attenuates the uniform light intensity through the structural parameters, and fuses the display effect of the structure area with the effect of traditional three-dimensional ultrasound surface imaging to obtain a better rendering effect, so that users can diagnose tissues more clearly and intuitively through three-dimensional images, strengthen the structural relationship between tissues, highlight the structural contours, and make the overall effect of the fused image more realistic, so as to achieve the purpose of optimizing rendering imaging.

[0095] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for rendering and imaging ultrasound volume data, characterized in that: The steps include: Acquire raw data of three-dimensional volume data; Interpolating and reconstructing the original data of the three-dimensional volume data to obtain voxels corresponding to the three-dimensional volume data and transparency parameters corresponding to the voxels; Acquire a two-dimensional rendering of the three-dimensional volume data according to the voxel and the transparency parameter; Extracting the bright and dark attenuation coefficient of the tissue structure contour under the same light beam in the three-dimensional volume data according to the voxel and transparency parameter, and obtaining a contour structure rendering image of the three-dimensional volume data according to the bright and dark attenuation coefficient of the tissue structure contour; Merging the two-dimensional rendering of the three-dimensional volume data with the contour structure rendering to obtain a desired image and display it; The step of extracting the light and dark attenuation coefficient of the tissue structure contour under the same light in the three-dimensional volume data according to the voxel and the transparency parameter, and obtaining the contour structure rendering image of the three-dimensional volume data according to the light and dark attenuation coefficient of the tissue structure contour specifically includes: Determine the number n1 of points that pass through the three-dimensional volume data under a light beam, wherein the n1 points are all points whose voxels are greater than a preset voxel threshold; Counting the average transparency of n2 points around each of the n1 points selected, and determining the light attenuation coefficient of each of the n1 points according to the average transparency; According to the transparency of each point in the n1 points, weighted accumulation is performed on the light attenuation coefficients of the n1 points to obtain the bright and dark attenuation coefficients on the light beam; The bright and dark attenuation coefficients on the light beam are optimized to obtain the final bright and dark attenuation coefficients of the tissue structure contour, and then the bright and dark attenuation coefficients of the tissue structure contour are normalized; Performing color mapping on the normalized tissue structure contour light and dark attenuation coefficients to obtain a contour structure rendering of the three-dimensional volume data; The calculation formula for the light attenuation coefficient of each point among n1 points is: ， Among them, at n is the average transparency of the n2 points around the nth point among the n1 points, ak n is the light attenuation coefficient of the nth point among n1 points, and the value of n ranges from 0 to n1; The calculation formula of the bright and dark attenuation coefficient on the light beam is: ， Among them, ak1 n is the brightness attenuation coefficient before accumulation, ak1 n+1 is the accumulated brightness and darkness attenuation coefficient, ak n is the light attenuation coefficient of the nth point among n1 points, sum.w n is the accumulated transparency value of n1 points; The calculation formula of the final tissue structure contour light and dark attenuation coefficient is: ， Among them, ak2 is the final tissue structure contour brightness attenuation coefficient, ak1 is the light attenuation coefficient, a, b, m1 and m2 are empirical parameters, and fak(ak1) is the brightness optimization function.

2. The ultrasound volume data rendering imaging method according to claim 1, characterized in that: The voxel preset threshold is 0.

02.

3. The ultrasound volume data rendering imaging method according to claim 1, characterized in that: The calculation formula for the mean transparency of n2 points is: ， Among them, at n is the average transparency of n2 points around the nth point among n1 points, aw i is the transparency of the i-th point among n2 points, where n2 is a natural number.

4. The ultrasound volume data rendering imaging method according to claim 1, characterized in that: The two-dimensional rendering of the three-dimensional volume data is fused with the contour structure rendering using the following formula: ， Among them, Pag is the two-dimensional rendering of the three-dimensional volume data, Pam is the contour structure rendering, P is the required image, and a1 and a2 are empirical constants.

5. An ultrasound volume data rendering imaging device, characterized in that: include: Processor and memory; The memory stores a computer-readable program executable by the processor; When the processor executes the computer-readable program, the steps in the ultrasound volume data rendering imaging method according to any one of claims 1 to 4 are implemented.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the ultrasound volume data rendering imaging method according to any one of claims 1 to 4.

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