Three-dimensional image slice layer number determination method and device, medium and equipment

Abstract

The invention discloses a three-dimensional image slice layer number determination method and device, a medium and equipment, and relates to the technical field of three-dimensional display imaging. The method comprises the following steps: determining a left neighborhood slice layer number N-n and a right neighborhood slice layer number N + n according to an initial slice layer number N and an initial search range n; acquiring restored three-dimensional images corresponding to the number of layers N, N-n and N + n, acquiring two-dimensional plane images of the restored three-dimensional images from different angles, and acquiring characteristic values for representing the quality of the restored three-dimensional images according to pixel distribution conditions in the two-dimensional plane images at different angles; and taking the slice layer number with the optimal characteristic value as a new initial slice layer number, and repeating the operation until the optimal slice layer number is obtained. By analyzing the pixel distribution in the two-dimensional plane image of the restored three-dimensional image acquired at different angles, the quality of the restored three-dimensional image can be quantified more comprehensively and accurately, so that the slice number which enables the imaging mechanical efficiency to be maximized and the imaging effect to be optimal is obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional display imaging, and in particular to a method, device, medium and equipment for determining the number of slice layers of a three-dimensional image. Background Art

[0002] The technology based on slice reconstruction first scans the object to be displayed in three dimensions through computer tomography (CT) or other three-dimensional scanning technology to obtain its three-dimensional data. A three-dimensional model is established through the three-dimensional data, and then the three-dimensional model is divided into a series of parallel two-dimensional slices using software, each of which represents the cross-section of the object to be displayed at a certain depth. Then, electronic display technology such as a projector is used to sequentially project the two-dimensional slices of different layers onto a "curtain" at different depths to restore the three-dimensional model. This method has a wide range of applications in fields such as geological exploration and industrial design. The resolution of the slice projection direction of the restored three-dimensional model is determined by the number of slice layers: when the number of slice layers is small, the restored imaging result is stable but the resolution is low, and the details and features of the three-dimensional model cannot be better displayed; when the number of slice layers is large, the image resolution will become higher, but the imaging result will be unstable due to the mechanical frequency of the scanning galvanometer reaching its limit. Therefore, how to obtain the optimal number of slice layers is of great significance to the resolution of the restored three-dimensional model.

[0003] Since the restored three-dimensional image is restored by projecting it onto a "curtain" at different depths, it is difficult to obtain the voxels (the smallest unit that makes up the three-dimensional image) in the restored three-dimensional image, and therefore it is difficult to quantify the quality of the restored three-dimensional image. As a result, the number of slices is currently determined mainly based on human eye observation and analysis of the imaging quality of the restored three-dimensional image. The operator decides the number and position of each slice by directly checking the clarity of the restored three-dimensional image.

[0004] However, the subjectivity of human observation makes it difficult to accurately evaluate the restoration quality of three-dimensional images. Different operators may obtain inconsistent slicing results on the same data, making it difficult to maximize the efficiency of the imaging machine while ensuring the imaging effect. Summary of the invention

[0005] Based on this, it is necessary to provide a method, device, medium and equipment for determining the number of slice layers of a three-dimensional image in order to solve the above technical problems.

[0006] This manual adopts the following technical solutions:

[0007] This specification provides a method for determining the number of slice layers of a three-dimensional image, comprising:

[0008] Determine the initial slice layer number N and the initial search range n, both of which are positive integers, and determine the left neighboring slice layer number Nn and the right neighboring slice layer number N+n according to the initial slice layer number N and the initial search range n;

[0009] Restored 3D images corresponding to the initial slice layer number N, the left neighbor slice layer number Nn, and the right neighbor slice layer number N+n are obtained respectively, and 2D plane images corresponding to the restored 3D images are collected from different angles, and characteristic values ​​used to characterize the quality of each restored 3D image are obtained according to the pixel connectivity or edge pixel density in the 2D plane images at different angles;

[0010] The number of slice layers corresponding to the optimal eigenvalue is used as the new initial number of slice layers, and the initial search range is narrowed; the eigenvalue acquisition operation is repeated according to the new initial number of slice layers and the reduced initial search range until the fluctuation of the eigenvalue is less than the set threshold, and the optimal number of slice layers is obtained.

[0011] Furthermore, the characteristic value includes a connectivity characteristic value P1 for characterizing the connectivity of voxels in the three-dimensional image, specifically including:

[0012] Collect two-dimensional plane images of the restored three-dimensional image corresponding to the slice layer number i from different angles;

[0013] Use the connected domain analysis method to obtain the number of connected pixel sets in each two-dimensional plane image;

[0014] Take the weighted sum of the number of connected pixel sets to obtain the eigenvalue P1 corresponding to the slice layer number i:

[0015] P1=(n 1 +n 2 +…+n J ) / J

[0016] Among them, n 1 ~n J are the numbers of connected pixel sets in the J two-dimensional plane images obtained from J angles respectively. The above formula means that the quality of the restored three-dimensional image is characterized by the number of connected pixel sets at different angles: the larger the number of connected pixel sets in each two-dimensional plane image, the more dispersed the voxels in the restored three-dimensional image, and the worse the restoration quality; the smaller the number of connected pixel sets in each two-dimensional plane image, the more dispersed the voxels in the restored three-dimensional image, and the better the restoration quality.

[0017] Furthermore, the characteristic value includes an edge characteristic value P2 for characterizing the edge clarity of the three-dimensional image, specifically including:

[0018] Collect two-dimensional plane images of the restored three-dimensional image corresponding to the slice layer number i from different angles;

[0019] Obtain edge pixel density in each two-dimensional plane image based on an edge detection algorithm;

[0020] Take the weighted sum of all edge pixel densities to obtain the eigenvalue P2 corresponding to the slice layer number i:

[0021] P2=(m 1 +m 2 +…+m J ) / J

[0022] Among them, m 1 ~m J are the edge pixel densities in J two-dimensional plane images obtained from J angles respectively. The above formula means that the quality of the restored three-dimensional image is characterized by the edge pixel density at different angles: the greater the edge pixel density in each two-dimensional plane image, the clearer the edge in the restored three-dimensional image and the better the restoration quality; the smaller the edge pixel density in each two-dimensional plane image, the blurred the edge in the restored three-dimensional image and the worse the restoration quality.

[0023] Furthermore, the restored three-dimensional image is obtained by scanning the shaped linear light source in the display material using a scanning galvanometer to form a continuous multi-layer screen, and projecting different sections of the three-dimensional model in sequence onto different screens through a digital micromirror display.

[0024] Furthermore, the wavelength of the linear light source is 1550 nm, and the curtain is a single-frequency excited curtain formed along the path when the linear light source passes through tellurite glass doped with trivalent erbium ions Er3+.

[0025] Furthermore, the digital micromirror display projects a pattern formed by irradiating a light source with a wavelength of 850 nm into a tellurite glass doped with trivalent erbium ions Er3+, thereby forming a dual-frequency excitation on the screen to produce a green pattern.

[0026] A device for determining the number of slice layers of a three-dimensional image, comprising:

[0027] A search initialization module is used to determine the initial slice layer number N and the initial search range n, where N and n are both positive integers, and to determine the left neighboring slice layer number Nn and the right neighboring slice layer number N+n according to the initial slice layer number N and the initial search range n;

[0028] The quality evaluation module is used to respectively obtain the restored 3D images corresponding to the initial slice layer number N, the left neighbor slice layer number Nn and the right neighbor slice layer number N+n, collect the 2D plane images corresponding to the restored 3D images from different angles, and obtain the characteristic values ​​used to characterize the quality of each restored 3D image according to the pixel connectivity or edge pixel density in the 2D plane images at different angles;

[0029] The module for determining the number of slice layers is used to use the number of slice layers corresponding to the optimal eigenvalue as the new initial number of slice layers and narrow the initial search range; the eigenvalue acquisition operation is repeated according to the new initial number of slice layers and the reduced initial search range until the fluctuation of the eigenvalue is less than the set threshold, thereby obtaining the optimal number of slice layers.

[0030] The present specification provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method for determining the number of slice layers of a three-dimensional image is implemented.

[0031] The present specification provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for determining the number of slice layers of a three-dimensional image when executing the program.

[0032] At least one of the above technical solutions adopted in this specification can achieve the following beneficial effects:

[0033] The present invention can obtain more comprehensive multi-angle views of the restored three-dimensional image by collecting two-dimensional plane images corresponding to the restored three-dimensional image from different angles. By analyzing the pixel distribution in the two-dimensional plane images at different angles, the restoration conditions of the restored three-dimensional image at different angles can be quantified, thereby more comprehensively and accurately evaluating the quality of the restored three-dimensional image. The number of slice layers is adjusted based on the evaluation result, so as to obtain the number of slices that maximizes the mechanical efficiency of imaging and achieves the best imaging effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0035] Figure 1 A schematic diagram of a method for determining the number of slice layers of a three-dimensional image provided in this specification;

[0036] Figure 2 It is the principle diagram provided in this manual for restoring a three-dimensional model by using two-dimensional slices of a three-dimensional model;

[0037] Figure 3 This is the principle diagram of restoring a cube with a side length of M from N layers of two-dimensional slices provided in this specification;

[0038] Figure 4 This is the principle diagram of restoring a cube with a side length of M from Nn layers of two-dimensional slices provided in this specification;

[0039] Figure 5This is the principle diagram of restoring a cube with a side length of M from N+n layers of two-dimensional slices provided in this specification;

[0040] Figure 6 It is the two-dimensional plane corresponding to the cube with different layers collected from the same angle and displayed by the volume three-dimensional imaging technology provided in this specification; (a), (b), (c), (d) and (e) correspond to the imaging results of the 15th, 20th, 25th, 30th and 35th slices of the cube figure respectively;

[0041] Figure 7 are the projected vertical stripes and horizontal stripes provided in this specification; (a) and (b) are vertical stripes and horizontal stripes with a resolution of 1280×800; (c) and (d) are vertical stripes and horizontal stripes with a resolution of 800×25;

[0042] Figure 8 This is a schematic diagram of imaging based on the dual-frequency up-conversion principle and using a scanning galvanometer and a digital micromirror device provided in this manual.

[0043] Description of reference numerals:

[0044] 1-digital micromirror device, 2-imaging lens group, 3-projection light, 4-tellurate glass doped with trivalent erbium ions Er3+, 5-linear light source, 6-scanning galvanometer. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of this specification more clear, the technical solutions of the present invention will be clearly and completely described below in combination with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments in the specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Example 1

[0047] The method provided in this embodiment is based on the principle of restoring a three-dimensional model by slicing a volumetric three-dimensional display, and optimizes the slice parameters that affect the image resolution and brightness. This method can be used in the fields of true three-dimensional display technology imaging. True three-dimensional display technology is widely used in military simulation, medical imaging, industrial design, flight simulators, advertising, movies, and exhibitions. For many application scenarios, factors that affect the restoration effect include image resolution, brightness, etc. Due to the limitations of current technology, the imaging quality has encountered a bottleneck. On this basis, this embodiment optimizes the slice parameters of the current volumetric three-dimensional display imaging, thereby improving the imaging quality.

[0048] In true 3D display technology, for example, static volume 3D display based on dual-frequency up-conversion has the following imaging characteristics: First, it uses dual-frequency infrared light source to generate visible green light, and infrared invisible light will not affect the display effect during the imaging process. Second, the display material must have good transparency and luminous efficiency. Third, the imaging method uses devices such as scanning galvanometers and digital micromirror display systems to restore the 3D model through 2D slices of the 3D model.

[0049] In the imaging method, a dual galvanometer is used to focus two light sources on the same point. The voxel point has high brightness, but due to the limitation of mechanical frequency, the image resolution presented in the display material is low, the voxel points are few, and it is difficult to form a complex image display. Using two digital micromirror displays for imaging, the spot energy of a beam of light is distributed on the entire two-dimensional plane. Although there are many voxel points, the brightness of the three-dimensional image presented is very low due to the low luminous efficiency of the luminescent material. Combining the advantages of the above two methods, a scanning galvanometer plus a digital micromirror display method is used. The scanning galvanometer is used to quickly scan the shaped linear light source in the display material to form a layer of continuous "curtains". Then, the three-dimensional model is projected on different "curtains" in sequence through the digital micromirror display to restore the three-dimensional model. The resolution of one dimension of this method depends on the number of slices. In theory, for the same display volume, the more layers, the clearer and the higher the resolution. The current slicing methods include continuous parallel plane slicing and rotating plane slicing, but the number of slices has not been discussed.

[0050] Based on this, this embodiment provides a method for improving the resolution of static volume 3D display. When restoring a 3D model using a slicing method, the resolution of a certain dimension is determined by the number of slices. This embodiment uses the imaging principle to find the maximum number of slice layers under the condition of stable display of the 3D image by exerting the maximum mechanical frequency to improve the volume 3D display resolution.

[0051] Figure 1 The flow chart of the method for determining the number of slice layers of a three-dimensional image in this embodiment is shown. Figure 1 The method for determining the number of slice layers of a three-dimensional image is described in detail, and specifically comprises the following steps:

[0052] S101: Determine an initial slice layer number N and an initial search range n, where both N and n are positive integers. According to the initial slice layer number N and the initial search range n, determine a left neighboring slice layer number Nn and a right neighboring slice layer number N+n.

[0053] The principle of restoring a 3D model by rapid sequential projection of 2D slices is as follows Figure 2The resolution in the XZ plane is determined by the digital microcrystalline device, while the resolution in the YZ plane is determined by the number of slice layers. In theory, for the same display volume, the more layers there are, the higher the resolution. The principle of improving resolution by optimizing the number of slice layers is as follows: Figure 3 , 4 , as shown in Figure 5.

[0054] Figure 3 The cube with side length M is restored by N slices. When the initial slice number is N, the spacing between each slice layer is L1 = M / N. The imaging results of different slice numbers are made on the left and right of the Nth layer for comparison. It should be noted that since the target volume displayed by the imaging does not change, when the slice number changes, the corresponding spacing between each layer also changes. For example Figure 4 As shown in , when the number of layers is Nn, the corresponding interlayer spacing is L2 = M / Nn. Similarly, when the model is sliced ​​into N+n layers, the corresponding interlayer spacing is L3 = M / N+n, as shown in Figure 5 shown.

[0055] S102: respectively obtain restored 3D images corresponding to the initial slice layer number N, the left neighbor slice layer number Nn and the right neighbor slice layer number N+n, collect 2D plane images of the restored 3D images from different angles, and obtain feature values ​​for characterizing the quality of the restored 3D images according to pixel distribution in the 2D plane images at different angles.

[0056] The eigenvalue includes a connectivity eigenvalue P1 for characterizing the connectivity of voxels in the three-dimensional image, specifically including: collecting two-dimensional plane images of the restored three-dimensional image corresponding to the slice layer number i from different angles; using the connected domain analysis method to obtain the number of connected pixel sets in each two-dimensional plane image; and performing weighted summation of the number of all connected pixel sets to obtain the eigenvalue P1 corresponding to the slice layer number i:

[0057] P1=(n 1 +n 2 +…+n J ) / J

[0058] Among them, n 1 ~n J are the numbers of connected pixel sets in the J two-dimensional plane images obtained from J angles respectively. The above formula means that the quality of the restored three-dimensional image is characterized by the number of connected pixel sets at different angles: the larger the number of connected pixel sets in each two-dimensional plane image, the more dispersed the voxels in the restored three-dimensional image, and the worse the restoration quality; the smaller the number of connected pixel sets in each two-dimensional plane image, the more dispersed the voxels in the restored three-dimensional image, and the better the restoration quality. Figure 6 The 2D planes corresponding to cubes of different layers collected from the same angle are displayed using volumetric 3D imaging technology. Figure 6(a), (b), (c), (d), and (e) correspond to the imaging results of 15, 20, 25, 30, and 35 slices of the cube graphic, respectively. When the cube is divided into only 15 layers, the image is incomplete, resulting in a significant loss of details. When the number of layers increases to 20, the effect is slightly improved, but some graphic features are still missing. At 30 layers, the image begins to flicker, and when the number of layers reaches 35, the flickering phenomenon intensifies. This is due to the limitation of the scanning frequency of hardware such as the scanning galvanometer and projection system, which makes the displayed image flicker and unstable. Experimental data show that 25-layer segmentation provides the most favorable balance, the pixels in the resulting image are the least dispersed, and the restoration quality is the best among them.

[0059] The above-mentioned eigenvalues ​​also include an edge eigenvalue P2 for characterizing the edge clarity of the three-dimensional image, which specifically includes: collecting two-dimensional plane images of the restored three-dimensional image corresponding to the slice layer number i from different angles; obtaining the edge pixel density in each two-dimensional plane image based on the edge detection algorithm; and performing weighted summation of all edge pixel densities to obtain the eigenvalue P2 corresponding to the slice layer number i:

[0060] P2=(m 1 +m 2 +…+m J ) / J

[0061] Among them, m 1 ~m J are the edge pixel densities in J two-dimensional plane images acquired from J angles respectively. The meaning of the above formula is to characterize the quality of the restored three-dimensional image by the edge pixel density at different angles: the greater the edge pixel density in each two-dimensional plane image, the clearer the edge in the restored three-dimensional image and the better the restoration quality; the smaller the edge pixel density in each two-dimensional plane image, the blurrier the edge in the restored three-dimensional image and the worse the restoration quality. The resolution is estimated by projecting horizontal and vertical stripes to determine the minimum spacing required to distinguish the two strips. When a microelectronic device DMD with a resolution of 1280×800 is used for projection and the number of slice layers is 25, the voxel volume of the volumetric three-dimensional display system is 1280×800×25. Vertical and horizontal stripes are projected on a plane with a resolution of 1280×800, and photos are taken to record the photos that can just distinguish the two stripes. Figure 7 (a) and Figure 7 (b) in the figure shows vertical and horizontal stripes with a resolution of 1280×800, which determines that the resolution in the vertical and horizontal directions is about 300 microns. Then the vertical and horizontal stripes are projected on a plane with a resolution of 800×25. Figure 7 (c) and Figure 7(d) in the figure shows vertical and horizontal stripes with a resolution of 800×25, and it is determined that the resolution in the vertical and horizontal directions is approximately 400 μm and 300 μm, respectively.

[0062] S103: taking the number of slice layers with the best eigenvalue as the new initial number of slice layers and reducing the initial search range; repeating the operation according to the new initial number of slice layers and the reduced initial search range until the fluctuation of the eigenvalue is less than the set threshold, and obtaining the optimal number of slice layers.

[0063] By observing the display effects under three groups of different numbers of slice layers, if the number of layers is N, the display effect is most stable and clear relative to the Nn layer and the N+n layer, then continue to narrow the range on the left and right sides of the N layer to find the most stable and clear slice layer; if the Nn layer or the N+n layer is the most stable and clear, continue to search in the same way, and finally find the slice layer with the largest number of slices under the condition of clear and stable imaging results to ensure higher resolution.

[0064] When the number of layers is less than the optimal number, the image effect is stable, but the resolution is low and cannot better display the details and features of the 3D model; when the number of layers is more than the optimal number, the image is unstable and unclear because the mechanical frequency of the scanning galvanometer has reached its limit and cannot produce a higher frequency scan.

[0065] In summary, this embodiment is based on a dual-optical path imaging system of a scanning galvanometer and a digital micromirror device, which optimizes the number of slice layers in the process of restoring a three-dimensional model from two-dimensional slices of a three-dimensional model, so as to ensure the resolution of the three-dimensional image with as many slice layers as possible.

[0066] Furthermore, in one or more embodiments of the present specification, the three-dimensional image is restored by scanning a shaped linear light source in a display material using a scanning galvanometer to form a continuous multi-layer screen, and projecting different sections of the three-dimensional model sequentially onto different screens through a digital micromirror display.

[0067] In the field of volumetric 3D display, static volumetric 3D display based on dual-frequency up-conversion has the advantages of stable and clear imaging, stable and flexible structure, etc. Tellurite glass doped with trivalent erbium ions Er3+ can absorb two infrared light beams with wavelengths of 850nm and 1550nm, respectively, and stimulate green fluorescence with a wavelength of 546nm. The principle of dual-frequency up-conversion is applied to volumetric 3D display. Two infrared light sources intersect in erbium-doped tellurite glass, and green visible fluorescence is generated at the intersection, which serves as the voxel point of volumetric 3D display. Then, the dual-optical path imaging method of scanning galvanometer plus digital micromirror device is combined for imaging.

[0068] like Figure 8As shown, a light source with a wavelength of 1550nm is shaped into a linear light source, which passes through the tellurite glass and forms a single-frequency excited "curtain" along the path; a light source with a wavelength of 850nm is irradiated on the digital microcrystalline display device, and the pattern on the digital microcrystalline display device is projected into the tellurite glass, and a dual-frequency excitation is formed on the "curtain" to produce a green visible pattern. The scanning galvanometer can quickly scan to produce continuous multi-layer "curtains" in the tellurite glass, and the digital micromirror device sequentially projects the two-dimensional slices of different layers of the three-dimensional model onto the "curtain" to restore the three-dimensional model.

[0069] Therefore, the number of voxel points of the final three-dimensional graphics is related to the number of slice layers and the parameters of the digital micromirror device. For example, if the number of slice layers is N and the parameters of the digital micromirror device are 1280×800, then the number of voxel points is N×1280×800. Therefore, the more slice layers there are, the more voxels there are, and the higher the resolution of the three-dimensional image. This manual maximizes the resolution of volumetric three-dimensional display by optimizing the number of slice layers.

[0070] The above is a method for determining the number of slice layers of a three-dimensional image provided by one or more embodiments of this specification. Based on the same idea, this specification also provides a corresponding device for determining the number of slice layers of a three-dimensional image, including:

[0071] The search initialization module is used to determine the initial slice layer number N and the initial search range n, where N and n are both positive integers. According to the initial slice layer number N and the initial search range n, the left neighbor slice layer number Nn and the right neighbor slice layer number N+n are determined.

[0072] The quality evaluation module is used to obtain the restored three-dimensional images corresponding to the initial slice layer number N, the left neighbor slice layer number Nn and the right neighbor slice layer number N+n, respectively, collect two-dimensional plane images of the restored three-dimensional image from different angles, and obtain characteristic values ​​for characterizing the quality of the restored three-dimensional image according to the pixel distribution in the two-dimensional plane images at different angles.

[0073] The slice layer number determination module is used to use the slice layer number with the best eigenvalue as the new initial slice layer number and reduce the initial search range; repeat the operation according to the new initial slice layer number and the reduced initial search range until the fluctuation of the eigenvalue is less than the set threshold, and obtain the optimal slice layer number.

[0074] For the specific definition of the device for determining the number of slice layers of a three-dimensional image, please refer to the definition of the method for determining the number of slice layers of a three-dimensional image above, which will not be repeated here. Each module in the above-mentioned device for determining the number of slice layers of a three-dimensional image can be implemented in whole or in part by software, hardware, and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0075] The present specification also provides a computer-readable storage medium, which stores a computer program. The computer program can be used to execute the above-mentioned method for determining the number of slice layers of a three-dimensional image.

[0076] This specification also provides the structure of a computer device. At the hardware level, the computer device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include hardware required for other services. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to implement the method for determining the number of three-dimensional image slice layers provided above.

[0077] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this specification can include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0078] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A method for determining the number of slice layers of a three-dimensional image, characterized in that: include: Determine the initial slice layer number N and the initial search range n, both of which are positive integers, and determine the left neighboring slice layer number Nn and the right neighboring slice layer number N+n according to the initial slice layer number N and the initial search range n; Restored 3D images corresponding to the initial slice layer number N, the left neighbor slice layer number Nn, and the right neighbor slice layer number N+n are obtained respectively, and 2D plane images corresponding to the restored 3D images are collected from different angles, and characteristic values ​​used to characterize the quality of each restored 3D image are obtained according to the pixel connectivity or edge pixel density in the 2D plane images at different angles; The number of slice layers corresponding to the optimal eigenvalue is used as the new initial number of slice layers, and the initial search range is narrowed; the eigenvalue acquisition operation is repeated according to the new initial number of slice layers and the reduced initial search range until the fluctuation of the eigenvalue is less than the set threshold, and the optimal number of slice layers is obtained.

2. A method for determining the number of slice layers of a three-dimensional image according to claim 1, characterized in that: The characteristic value includes a connectivity characteristic value P1 for characterizing the connectivity of voxels in the three-dimensional image, specifically including: Collect two-dimensional plane images of the restored three-dimensional image corresponding to the slice layer number i from different angles; Use the connected domain analysis method to obtain the number of connected pixel sets in each two-dimensional plane image; Take the weighted sum of the number of connected pixel sets to obtain the eigenvalue P1 corresponding to the slice layer number i: P1=(n 1 +n 2 +…+n J ) / J Among them, n 1 ~n J are the numbers of connected pixel sets in the J two-dimensional plane images obtained from J angles respectively. The above formula means that the quality of the restored three-dimensional image is characterized by the number of connected pixel sets at different angles: the larger the number of connected pixel sets in each two-dimensional plane image, the more dispersed the voxels in the restored three-dimensional image, and the worse the restoration quality; the smaller the number of connected pixel sets in each two-dimensional plane image, the more dispersed the voxels in the restored three-dimensional image, and the better the restoration quality.

3. The method for determining the number of slice layers of a three-dimensional image according to claim 1, characterized in that: The feature value includes an edge feature value P2 for characterizing the edge clarity of the three-dimensional image, specifically including: Collect two-dimensional plane images of the restored three-dimensional image corresponding to the slice layer number i from different angles; Obtain edge pixel density in each two-dimensional plane image based on an edge detection algorithm; Take the weighted sum of all edge pixel densities to obtain the eigenvalue P2 corresponding to the slice layer number i: P2=(m 1 +m 2 +…+m J ) / J Among them, m 1 ~m J are the edge pixel densities in J two-dimensional plane images obtained from J angles respectively. The above formula means that the quality of the restored three-dimensional image is characterized by the edge pixel density at different angles: the greater the edge pixel density in each two-dimensional plane image, the clearer the edge in the restored three-dimensional image and the better the restoration quality; the smaller the edge pixel density in each two-dimensional plane image, the blurred the edge in the restored three-dimensional image and the worse the restoration quality.

4. The method for determining the number of slice layers of a three-dimensional image according to claim 1, characterized in that: The restored three-dimensional image is obtained by scanning a shaped linear light source in a display material using a scanning galvanometer to form a continuous multi-layer screen, and projecting different sections of the three-dimensional model sequentially onto different screens through a digital micromirror display.

5. A method for determining the number of slice layers of a three-dimensional image as claimed in claim 4, characterized in that: The wavelength of the linear light source is 1550 nm, and the curtain is a single-frequency excited curtain formed along the path when the linear light source passes through tellurite glass doped with trivalent erbium ions Er3+.

6. A method for determining the number of slice layers of a three-dimensional image according to claim 5, characterized in that: The digital micromirror display projects a pattern formed by irradiating a light source with a wavelength of 850nm into a tellurite glass doped with trivalent erbium ions Er3+, thereby forming a dual-frequency excitation on the screen to generate a green pattern.

7. A device for determining the number of slice layers of a three-dimensional image, characterized in that: include: A search initialization module is used to determine the initial slice layer number N and the initial search range n, where N and n are both positive integers, and to determine the left neighboring slice layer number Nn and the right neighboring slice layer number N+n according to the initial slice layer number N and the initial search range n; The quality evaluation module is used to respectively obtain the restored 3D images corresponding to the initial slice layer number N, the left neighbor slice layer number Nn and the right neighbor slice layer number N+n, collect the 2D plane images corresponding to the restored 3D images from different angles, and obtain the characteristic values ​​used to characterize the quality of each restored 3D image according to the pixel connectivity or edge pixel density in the 2D plane images at different angles; The module for determining the number of slice layers is used to use the number of slice layers corresponding to the optimal eigenvalue as the new initial number of slice layers and narrow the initial search range; the eigenvalue acquisition operation is repeated according to the new initial number of slice layers and the reduced initial search range until the fluctuation of the eigenvalue is less than the set threshold, thereby obtaining the optimal number of slice layers.

8. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

9. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in any one of claims 1 to 6 is implemented.

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