Substance decomposition imaging method, device, equipment and medium of oral cavity dual-energy cone beam CT (Computed Tomography)

Abstract

The invention relates to the technical field of CT imaging, and discloses a substance decomposition imaging method, device, equipment and medium for oral cavity dual-energy cone beam CT, and the method comprises the steps: carrying out the projection angle compensation of high-energy and low-energy original data collected by the oral cavity dual-energy cone beam CT, and obtaining high-energy and low-energy compensation data; performing three-dimensional reconstruction on the high and low energy compensation data to obtain a high and low energy volume attenuation image; performing non-local mean filtering on the high and low energy volume attenuation image to obtain a high and low energy volume attenuation filtering image; performing substance coefficient decomposition on the high-energy and low-energy volume attenuation filtering image to obtain a decomposition coefficient image; and generating a substance decomposition image according to the decomposition coefficient image. According to the invention, the accuracy of substance decomposition imaging of oral cavity dual-energy cone beam CT can be improved.

Description

Technical Field

[0001] The present invention relates to the field of CT imaging technology, and in particular to a material decomposition imaging method, device, equipment and medium for oral dual-energy cone-beam CT. Background Art

[0002] Cone-beam computed tomography (CBCT) has the advantages of high resolution and low radiation dose and is widely used in oral and maxillofacial imaging examinations. However, in oral and maxillofacial imaging examinations, the tooth density is usually very high and patients often have metal objects such as dental crowns, resulting in serious cone-beam CT image artifacts.

[0003] Compared with cone-beam CT, dual-energy cone-beam CT can provide two energies, thus providing more information than traditional monoenergetic CT and generating virtual monoenergetic (VM) images. These images can provide enhanced contrast and reduce imaging artifacts, have better artifact suppression effects, and have higher image information accuracy. However, there are currently very few studies on dual-energy imaging methods for oral examinations. Therefore, how to realize the calculation of energy spectrum images during oral examinations to obtain high-quality energy spectrum images with rich quantitative information has become an urgent problem to be solved. Summary of the invention

[0004] The present invention provides a material decomposition imaging method, device, equipment and medium for oral dual-energy cone-beam CT, the main purpose of which is to solve the problem of poor accuracy of material decomposition imaging for oral dual-energy cone-beam CT.

[0005] To achieve the above object, the present invention provides a material decomposition imaging method for oral dual-energy cone-beam CT, comprising:

[0006] Acquire high-energy and low-energy original data acquired by oral dual-energy cone-beam CT, perform projection angle compensation on the high-energy and low-energy original data, and obtain high- and low-energy compensated data;

[0007] Performing three-dimensional reconstruction on the high and low energy compensation data to obtain high and low energy volume attenuation images;

[0008] Performing non-local mean filtering on the high and low energy volume attenuation images to obtain high and low energy volume attenuation filtered images;

[0009] Performing material coefficient decomposition on the high and low energy volume attenuation filter images to obtain decomposition coefficient images;

[0010] A material decomposition image corresponding to the high-energy and low-energy original data is generated according to the decomposition coefficient image.

[0011] Optionally, performing projection angle compensation on the high-energy and low-energy original data to obtain high- and low-energy compensated data includes:

[0012] Performing projection conversion on the high-energy and low-energy original data to obtain high-energy projection data and low-energy projection data;

[0013] The high energy and low energy raw data are projected and transformed using the following formula:

[0014]

[0015] Wherein, p represents high-energy projection data or low-energy projection data, s0 represents the number of incident photons of oral dual-energy cone-beam CT, and s represents the number of outgoing photons in the high-energy or low-energy raw data;

[0016] Performing three-dimensional reconstruction on the high-energy projection data and the low-energy projection data to obtain a high-energy reconstructed volume image and a low-energy reconstructed volume image;

[0017] Performing two-dimensional conversion on the high-energy reconstructed volume image and the low-energy reconstructed volume image to obtain a high-energy forward projection image and a low-energy forward projection image;

[0018] Performing angle compensation on the high-energy and low-energy original data according to the high-energy forward projection image and the low-energy forward projection image to obtain high- and low-energy compensated data;

[0019] The high energy and low energy raw data are angle compensated using the following formula:

[0020]

[0021] Among them, p H represents the low energy compensation data in the high and low energy compensation data, p L represents the high energy compensation data in the high and low energy compensation data, p Hf represents the high energy forward projection image, p Lf represents the low energy forward projection image.

[0022] Optionally, the three-dimensional reconstruction of the high and low energy compensation data to obtain high and low energy volume attenuation images includes:

[0023] Performing ramp filtering on the high and low energy compensation data to obtain filtered data;

[0024] The filtered data is weighted back-projected to obtain high and low energy volume attenuation images.

[0025] Optionally, performing non-local mean filtering on the high and low energy volume attenuation images to obtain high and low energy volume attenuation filtered images includes:

[0026] Traversing the pixel points in the high-energy and low-energy volume attenuation images respectively, and selecting one pixel point at a time as a central pixel point;

[0027] Initializing a search pixel block and a neighborhood pixel block in the high and low energy volume attenuation image according to the central pixel point;

[0028] Calculate the local pixel weight of the central pixel according to the search pixel block and the neighborhood pixel block;

[0029] The pixel local weight of the central pixel is calculated using the following formula:

[0030]

[0031] Wherein, m represents the central pixel point, n represents any pixel point in the search pixel block V(m), V(n) represents the neighborhood pixel block formed by the neighborhood of pixel point n, V(m) represents the search pixel block formed by the neighborhood of pixel point m, e represents a natural constant, q represents a preset adjustable control coefficient, and w(m,n) represents the local weight of the pixel corresponding to the central pixel point in the neighborhood pixel block and the search pixel block;

[0032] Performing weighted averaging on the search pixel block according to the pixel local weight to obtain a target pixel value;

[0033] The pixel value of the central pixel is replaced by the target pixel value to obtain a high- and low-energy volume attenuation filter image.

[0034] Optionally, performing weighted averaging on the search pixel block according to the local pixel weight to obtain a target pixel value includes:

[0035] The target pixel value is obtained by weighted averaging the search pixel block using the following formula:

[0036]

[0037] Among them, v′(m) represents the target pixel value of the center pixel point m, V(m) represents the search pixel block composed of the neighborhood of pixel point m, n represents any pixel point in the search pixel block V(m), w(m,n) represents the local pixel weight of the center pixel point, and v(m) represents the pixel value of the center pixel point m.

[0038] Optionally, performing material coefficient decomposition on the high and low energy volume attenuation filter images to obtain decomposition coefficient images includes:

[0039] Acquire a base material attenuation coefficient corresponding to a preset base material, and construct a decomposition equation group according to the base material attenuation coefficient and the high and low energy volume attenuation filter images;

[0040] The decomposed equations are expressed as:

[0041]

[0042] Among them, μ h , μ l Respectively represent the high-energy volume attenuation image and the low-energy volume attenuation image in the high-energy and low-energy volume attenuation images, μ 1h , μ 1l represent the mass attenuation coefficient of the first base material under high energy conditions and low energy conditions in the base material attenuation coefficient, μ 2h , μ 2l Respectively represent the mass attenuation coefficient of the second base material under high energy conditions and low energy conditions in the base material attenuation coefficient, ρ1 and ρ2 respectively represent the density values ​​of the first base material and the second base material in the base material attenuation coefficient, and A1 and A2 respectively represent the decomposition coefficient images corresponding to the first base material and the second base material;

[0043] The decomposition coefficient image corresponding to the base material is solved according to the decomposition equation group.

[0044] Optionally, generating material decomposition images corresponding to the high-energy and low-energy original data according to the decomposition coefficient images includes:

[0045] The material decomposition images corresponding to the high-energy and low-energy raw data are generated using the following formula:

[0046] δ D =A1μ 1D +A2μ 2D

[0047] σ d =A1σ d1 +A2σ d2

[0048] Among them, δ D represents the virtual monoenergetic image at the single energy level D in the material decomposition image, A1 and A2 represent the decomposition coefficient images of the first basis material and the second basis material corresponding to the decomposition coefficient image, respectively, μ 1D , μ 2D They represent the attenuation coefficients of the first basis material and the second basis material corresponding to the decomposition coefficient image at a single energy level D, σ d represents the electron density image at a single energy level d in the decomposition image of the substance, σ d1 , σ d2 They respectively represent the electron density values ​​of the first basis material and the second basis material corresponding to the decomposition coefficient image at a single energy level d.

[0049] In order to solve the above problems, the present invention also provides a material decomposition imaging device for oral dual-energy cone-beam CT, the device comprising:

[0050] A projection angle compensation module is used to obtain high-energy and low-energy original data collected by oral dual-energy cone-beam CT, perform projection angle compensation on the high-energy and low-energy original data, and obtain high- and low-energy compensated data;

[0051] A three-dimensional reconstruction module, used for performing three-dimensional reconstruction on the high and low energy compensation data to obtain high and low energy volume attenuation images;

[0052] A non-local mean filtering module, used for performing non-local mean filtering on the high and low energy volume attenuation images to obtain high and low energy volume attenuation filtered images;

[0053] A material coefficient decomposition module, used for performing material coefficient decomposition on the high and low energy volume attenuation filter image to obtain a decomposition coefficient image;

[0054] The material decomposition image generation module is used to generate the material decomposition images corresponding to the high-energy and low-energy original data according to the decomposition coefficient image.

[0055] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0056] at least one processor; and,

[0057] a memory communicatively connected to the at least one processor; wherein,

[0058] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the above-mentioned material decomposition imaging method of oral dual-energy cone-beam CT.

[0059] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one computer program is stored. The at least one computer program is executed by a processor in an electronic device to implement the above-mentioned material decomposition imaging method of oral dual-energy cone-beam CT.

[0060] The embodiment of the present invention can compensate for the missing angles of alternating high and low energy acquisition by compensating the projection angle of the high energy and low energy original data collected by the oral dual-energy cone beam CT, thereby obtaining more accurate high and low energy compensation data; the high and low energy volume attenuation images obtained by three-dimensional reconstruction of the high and low energy compensation data are subjected to non-local mean filtering, thereby effectively suppressing the noise in the high and low energy volume attenuation images and improving the image quality; the high and low energy volume attenuation filter images are subjected to material coefficient decomposition to obtain decomposition coefficient images; the material decomposition images are generated according to the decomposition coefficient images, thereby obtaining energy spectrum images with better image quality and rich quantitative information, thereby making the material decomposition imaging of the oral dual-energy cone beam CT more accurate. Therefore, the material decomposition imaging method, device, equipment and medium of the oral dual-energy cone beam CT proposed by the present invention can solve the problem of poor accuracy of material decomposition imaging of the oral dual-energy cone beam CT. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 A schematic flow chart of a material decomposition imaging method for oral dual-energy cone-beam CT provided by an embodiment of the present invention;

[0062] Figure 2 A schematic diagram of a process for alternately acquiring high and low energy projections of dual energy cone beam CT provided by an embodiment of the present invention;

[0063] Figure 3 A schematic diagram of a process for performing projection angle compensation on high-energy and low-energy raw data provided by an embodiment of the present invention;

[0064] Figure 4 A functional module diagram of a material decomposition imaging device for oral dual-energy cone-beam CT provided by an embodiment of the present invention;

[0065] Figure 5 A schematic diagram of the structure of an electronic device for implementing the material decomposition imaging method of oral dual-energy cone-beam CT provided by an embodiment of the present invention.

[0066] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0067] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0068] The embodiment of the present application provides a material decomposition imaging method for oral dual-energy cone-beam CT. The execution subject of the material decomposition imaging method for oral dual-energy cone-beam CT includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in the embodiment of the present application. In other words, the material decomposition imaging method for oral dual-energy cone-beam CT can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0069] Reference Figure 1 FIG. 1 is a flow chart of a material decomposition imaging method for oral dual-energy cone-beam CT provided by an embodiment of the present invention. In this embodiment, the material decomposition imaging method for oral dual-energy cone-beam CT includes:

[0070] S1. Acquire high-energy and low-energy original data collected by oral dual-energy cone-beam CT, perform projection angle compensation on the high-energy and low-energy original data, and obtain high- and low-energy compensated data.

[0071] In the embodiment of the present invention, the oral dual-energy cone-beam CT uses X-ray beams of different energies to scan the oral cavity to obtain more detailed oral image information. The oral dual-energy cone-beam CT realizes high- and low-energy projection alternating scanning and acquisition by rapidly switching KV (tube voltage Kilovolts) of the tube to obtain high-energy raw data sets and low-energy raw data. Specifically, the high- and low-energy projection alternating acquisition can be referred to Figure 2 shown.

[0072] Furthermore, dual-energy cone-beam CT uses two energy X-ray beams to scan the oral cavity through dual-energy imaging to obtain photon number information at different energies and obtain high-energy and low-energy original data.

[0073] In an embodiment of the present invention, there will be a certain angle difference in the scanning acquisition angles corresponding to the high-energy and low-energy projections. Therefore, the high-energy original data and the low-energy original data obtained after one scan will have missing projection angles, that is, the number of projection angles is insufficient, which is prone to undersampling artifacts and inaccurate reconstructed images. Therefore, it is necessary to perform angle projection compensation on the high-energy and low-energy original data to obtain more accurate high- and low-energy compensated data, wherein the high- and low-energy compensated data include angle compensation data corresponding to the high-energy original data and angle compensation data corresponding to the low-energy original data.

[0074] Specifically, see Figure 3 As shown, the projection angle compensation is performed on the high energy and low energy original data to obtain high and low energy compensation data, including:

[0075] S31, performing projection conversion on the high-energy and low-energy original data to obtain high-energy projection data and low-energy projection data;

[0076] S32, performing three-dimensional reconstruction on the high-energy projection data and the low-energy projection data to obtain a high-energy reconstructed volume image and a low-energy reconstructed volume image;

[0077] S33, performing two-dimensional conversion on the high-energy reconstructed volume image and the low-energy reconstructed volume image to obtain a high-energy forward projection image and a low-energy forward projection image;

[0078] S34, performing angle compensation on the high-energy and low-energy original data according to the high-energy forward projection image and the low-energy forward projection image to obtain high- and low-energy compensated data.

[0079] In the embodiment of the present invention, the projection conversion is to convert the photon number information in the high-energy and low-energy original data into a projection value corresponding to the attenuation coefficient.

[0080] Specifically, the high-energy and low-energy raw data are projected and transformed using the following formula:

[0081]

[0082] Wherein, p represents high-energy projection data or low-energy projection data, s0 represents the number of incident photons of oral dual-energy cone-beam CT, and s represents the number of outgoing photons in the high-energy or low-energy original data.

[0083] In the embodiment of the present invention, the three-dimensional reconstruction is to construct the high-energy projection data into the corresponding high-energy reconstructed volume image, and to construct the low-energy projection data into the corresponding low-energy reconstructed volume image, so as to realize the reconstruction of the original data. Specifically, the FDK (Feldkamp, ​​Davis, and Kress reconstruction algorithm) reconstruction algorithm can be used to perform three-dimensional reconstruction to obtain the high-energy reconstructed volume image and the low-energy reconstructed volume image.

[0084] Furthermore, the two-dimensional conversion is to use a forward projection operator to convert the high-energy reconstructed volume image and the low-energy reconstructed volume image of the three-dimensional space into a two-dimensional projection image, thereby obtaining a high-energy forward projection image and a low-energy forward projection image, wherein the ray-driven forward projection operator can be used to perform forward projection to realize the two-dimensional conversion of the three-dimensional space using the forward projection operator.

[0085] Specifically, the high-energy and low-energy raw data are angle compensated using the following formula:

[0086]

[0087] Among them, p H represents the low energy compensation data in the high and low energy compensation data, p L represents the high energy compensation data in the high and low energy compensation data, p Hf represents the high energy forward projection image, p Lf represents the low energy forward projection image.

[0088] In the embodiment of the present invention, the high- and low-energy compensation data include high-energy compensation data corresponding to the high-energy original data and low-energy compensation data corresponding to the low-energy original data. The high- and low-energy compensation data can be solved by the above formula.

[0089] Specifically, since high-energy and low-energy original data are acquired alternately, the high-energy and low-energy angles are also missing alternately. The missing angles can be compensated by complementing the high-energy and low-energy projection information to obtain more accurate high-energy and low-energy compensation data.

[0090] S2. Perform three-dimensional reconstruction on the high and low energy compensation data to obtain high and low energy volume attenuation images.

[0091] In an embodiment of the present invention, three-dimensional reconstruction is to reconstruct a three-dimensional model of the oral cavity based on more accurate high and low energy compensation data after projection angle compensation, so as to obtain more accurate high and low energy volume attenuation images, wherein the high and low energy volume attenuation images include a high energy volume attenuation image corresponding to the high energy compensation data and a low energy volume attenuation image corresponding to the low energy compensation data.

[0092] In an embodiment of the present invention, the three-dimensional reconstruction of the high and low energy compensation data to obtain high and low energy volume attenuation images includes:

[0093] Performing ramp filtering on the high and low energy compensation data to obtain filtered data;

[0094] The filtered data is weighted back-projected to obtain high and low energy volume attenuation images.

[0095] Among them, ramp filtering is a back-projection filtering method, which can be implemented by a preset ramp-shaped filtering function. The noise in the high and low energy compensation data can be reduced by ramp filtering.

[0096] Furthermore, weighted back projection is to back-project the filtered data to generate an intermediate image, namely, a high- and low-energy volume attenuation image, wherein back projection is an inverse process, converting the projection data (usually a two-dimensional X-ray image) back into the density distribution of a three-dimensional object, namely, reconstructing a three-dimensional high- and low-energy volume attenuation image, wherein the filtered data can be weighted back-projected using a preset back-projection formula according to the angle and distance during oral dual-energy cone-beam CT scanning.

[0097] S3. Perform non-local mean filtering on the high and low energy volume attenuation images to obtain high and low energy volume attenuation filtered images.

[0098] In the embodiment of the present invention, the high and low energy volume attenuation images after three-dimensional reconstruction may have noise and artifacts, and the noise can be suppressed by non-local mean filtering to improve the image quality of the high and low energy volume attenuation images.

[0099] Among them, the non-local mean filter (NLM) finds similar pixel blocks in the high- and low-energy volume attenuation images and calculates the mean of these blocks to replace the value of the target pixel. That is, it uses the non-local (i.e., far away from the target pixel) similarity in the high- and low-energy volume attenuation images to reduce noise while retaining the edge and detail information of the high- and low-energy volume attenuation images.

[0100] Specifically, performing non-local mean filtering on the high and low energy volume attenuation images to obtain high and low energy volume attenuation filtered images includes:

[0101] Traversing the pixel points in the high-energy and low-energy volume attenuation images respectively, and selecting one pixel point at a time as a central pixel point;

[0102] Initializing a search pixel block and a neighborhood pixel block in the high and low energy volume attenuation image according to the central pixel point;

[0103] Calculate the local pixel weight of the central pixel according to the search pixel block and the neighborhood pixel block;

[0104] Performing weighted averaging on the search pixel block according to the local pixel weight to obtain a target pixel value;

[0105] The pixel value of the central pixel is replaced by the target pixel value to obtain a high- and low-energy volume attenuation filter image.

[0106] In the embodiment of the present invention, each pixel point in the high-energy volume attenuation image and the low-energy volume attenuation image is traversed, and each pixel point is used as a central pixel point to filter the high-energy and low-energy volume attenuation images as a whole. The search pixel block is to search for an image block similar to the periphery of the central pixel point in the image where the central pixel point is located. The neighborhood pixel block is an adjacent pixel block of any pixel point in the search pixel block. For example, if the central pixel point is a pixel point in the high-energy volume attenuation image, an image block similar to the periphery of the central pixel point is searched in the high-energy volume attenuation image to obtain the search pixel block. At the same time, the neighborhood pixel block is obtained according to the adjacent pixel blocks of any pixel point in the search pixel block in the high-energy volume attenuation image.

[0107] Among them, the neighborhood pixel block and the search pixel block can be calculated based on different filtering neighborhood windows and filtering search windows. For example, the search window is 30*30*30, the neighborhood window is 3*3*3, and the pixel local weight is calculated by calculating the distance between each pixel point in the search pixel block and the neighborhood pixel block.

[0108] Specifically, the pixel local weight of the central pixel is calculated using the following formula:

[0109]

[0110] Among them, m represents the central pixel point, n represents any pixel point in the search pixel block V(m), V(n) represents the neighborhood pixel block composed of the neighborhood of pixel point n, V(m) represents the search pixel block composed of the neighborhood of pixel point m, e represents a natural constant, q represents a preset adjustable control coefficient, and w(m,n) represents the local weight of the pixels corresponding to the central pixel point in the neighborhood pixel block and the search pixel block.

[0111] Preferably, different adjustable control parameters can be set for the high-energy volume attenuation image and the low-energy volume attenuation image, respectively, and the local pixel weights can be calculated specifically for the high-energy volume attenuation image and the low-energy volume attenuation image. The central pixel points in the high-energy volume attenuation image and the low-energy volume attenuation image can be filtered, respectively, to improve the accuracy of non-local mean filtering of the high-energy volume attenuation image and the low-energy volume attenuation image.

[0112] Specifically, the search pixel block is weighted averaged using the following formula to obtain the target pixel value:

[0113]

[0114] Among them, v′(n) represents the target pixel value of the central pixel point m, V(m) represents the search pixel block composed of the neighborhood of pixel point m, n represents any pixel point in the search pixel block V(m), w(M,n) represents the local pixel weight of the central pixel point, and v(m) represents the pixel value of the central pixel point m.

[0115] In the embodiment of the present invention, each pixel in the high and low energy volume attenuation images can be filtered by non-local mean filtering, which can effectively suppress the noise in the high and low energy volume attenuation images, improve the image quality of the high and low energy volume attenuation images, and obtain high and low energy volume attenuation filtered images with better image quality.

[0116] S4. Perform material coefficient decomposition on the high and low energy volume attenuation filter images to obtain decomposition coefficient images.

[0117] In an embodiment of the present invention, the high- and low-energy volume attenuation filter images include a high-energy volume attenuation image obtained after non-mean filtering of the high-energy volume attenuation image and a low-energy volume attenuation image obtained after non-mean filtering of the low-energy volume attenuation image. The material coefficients of the high- and low-energy volume attenuation filter images are decomposed and the decomposition coefficients are calculated, thereby providing a basis for further generating a material decomposition image.

[0118] In the embodiment of the present invention, the material coefficient decomposition of the high and low energy volume attenuation filter image to obtain the decomposition coefficient image includes:

[0119] Acquire a base material attenuation coefficient corresponding to a preset base material, and construct a decomposition equation group according to the base material attenuation coefficient and the high and low energy volume attenuation filter images;

[0120] The decomposition coefficient image corresponding to the base material is solved according to the decomposition equation group.

[0121] In an embodiment of the present invention, the base material attenuation coefficient is the mass attenuation coefficient of the base material under high-energy and low-energy conditions, including the mass attenuation coefficients of two base materials (a first base material and a second base material). Two material materials can be selected as the base materials. For example, water and iodine are selected as the first base material and the second base material, respectively. A decomposition equation group including decomposition coefficients is constructed through the mass attenuation coefficients of the base material under high-energy and low-energy conditions, and then the decomposition coefficient image of the base material can be solved, that is, the decomposition coefficient image corresponding to the high and low energy volume attenuation filter image.

[0122] Specifically, the decomposed equation group is expressed as:

[0123]

[0124] Among them, μ h , μ l Respectively represent the high-energy volume attenuation image and the low-energy volume attenuation image in the high-energy and low-energy volume attenuation images, μ 1h , μ 1l represent the mass attenuation coefficient of the first base material under high energy conditions and low energy conditions in the base material attenuation coefficient, respectively, μ 2l They respectively represent the mass attenuation coefficient of the second base material under high energy conditions and low energy conditions in the base material attenuation coefficient, ρ1 and ρ2 respectively represent the density values ​​of the first base material and the second base material in the base material attenuation coefficient, A1 and A2 respectively represent the decomposition coefficient images corresponding to the first base material and the second base material.

[0125] Furthermore, by solving the decomposition equation group, the decomposition coefficient images A1 and A2 are obtained as shown below:

[0126]

[0127] Among them, A1 and A2 represent the decomposition coefficient images corresponding to the first base material and the second base material respectively, μ h , μ l respectively represent the high-energy volume attenuation image and the low-energy volume attenuation image in the high-energy and low-energy volume attenuation images, μ 1l represent the mass attenuation coefficient of the first base material under high energy conditions and low energy conditions in the base material attenuation coefficient, respectively, μ 2l They respectively represent the mass attenuation coefficient of the second base material under high energy conditions and low energy conditions in the base material attenuation coefficient.

[0128] In the embodiment of the present invention, a decomposition coefficient image under a base material can be obtained by material coefficient decomposition, and material coefficient decomposition can be performed on high- and low-energy volume attenuation filter images to obtain a better material decomposition image.

[0129] S5. Generate material decomposition images corresponding to the high-energy and low-energy original data according to the decomposition coefficient images.

[0130] In an embodiment of the present invention, the material decomposition image includes a virtual monoenergetic image and an electron density image, wherein the virtual monoenergetic image includes high and low energy image data of the oral cavity, which can reduce noise and artifacts in the image, improve the clarity and contrast of the image, and enhance the visualization effect of specific tissues (such as blood vessels and tumors) by selecting appropriate virtual energy levels; the electron density image is an image that can display the electron density of the oral cavity. The electron density image can help identify and distinguish different tissue types, and can also highlight the differences in electron density, enhance the contrast of the image, and make subtle oral lesions easier to identify.

[0131] Specifically, generating the material decomposition image corresponding to the high-energy and low-energy original data according to the decomposition coefficient image includes:

[0132] The material decomposition images corresponding to the high-energy and low-energy raw data are generated using the following formula:

[0133] δ D =A1μ 1D +A2μ 2D

[0134] σ d =A1σ d1 +A2σ d2

[0135] Among them, δ Drepresents the virtual monoenergetic image at the single energy level D in the material decomposition image, A1 and A2 represent the decomposition coefficient images of the first basis material and the second basis material corresponding to the decomposition coefficient image, respectively, μ 1D , μ 2D They represent the attenuation coefficients of the first basis material and the second basis material corresponding to the decomposition coefficient image at a single energy level D, σ d represents the electron density image at a single energy level d in the decomposition image of the substance, σ d1 , σ d2 They respectively represent the electron density values ​​of the first basis material and the second basis material corresponding to the decomposition coefficient image at a single energy level d.

[0136] Among them, the material decomposition image represents the virtual monoenergetic image and electron density image at different energy levels. By selecting different virtual energies, the material decomposition images of different energy levels under a single energy level can be obtained.

[0137] In the embodiment of the present invention, a single energy spectrum image can be obtained through the material decomposition image, which has a better artifact suppression effect, and the energy spectrum image with better image quality and rich quantitative information makes the material decomposition imaging of oral dual-energy cone-beam CT more accurate.

[0138] like Figure 4 , which is a functional module diagram of a material decomposition imaging device for oral dual-energy cone-beam CT provided by an embodiment of the present invention.

[0139] The material decomposition imaging device 400 for oral dual-energy cone-beam CT of the present invention can be installed in an electronic device. According to the functions to be implemented, the material decomposition imaging device 400 for oral dual-energy cone-beam CT can include a projection angle compensation module 401, a three-dimensional reconstruction module 402, a non-local mean filtering module 403, a material coefficient decomposition module 404 and a material decomposition image generation module 405. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by a processor of an electronic device and can complete fixed functions, which are stored in the memory of the electronic device.

[0140] In this embodiment, the functions of each module / unit are as follows:

[0141] The projection angle compensation module 401 is used to obtain high-energy and low-energy original data acquired by oral dual-energy cone-beam CT, perform projection angle compensation on the high-energy and low-energy original data, and obtain high- and low-energy compensated data;

[0142] The three-dimensional reconstruction module 402 is used to perform three-dimensional reconstruction on the high and low energy compensation data to obtain high and low energy volume attenuation images;

[0143] The non-local mean filtering module 403 is used to perform non-local mean filtering on the high and low energy volume attenuation images to obtain high and low energy volume attenuation filtered images;

[0144] The material coefficient decomposition module 404 is used to perform material coefficient decomposition on the high and low energy volume attenuation filter image to obtain a decomposition coefficient image;

[0145] The material decomposition image generating module 405 is used to generate material decomposition images corresponding to the high-energy and low-energy original data according to the decomposition coefficient image.

[0146] In detail, the modules described in the material decomposition imaging device 400 for oral dual-energy cone-beam CT described in the embodiment of the present invention adopt the same technical means as the material decomposition imaging method for oral dual-energy cone-beam CT described in the above-mentioned drawings when in use, and can produce the same technical effects, which will not be repeated here.

[0147] like Figure 5 , which is a schematic diagram of the structure of an electronic device for implementing a material decomposition imaging method of oral dual-energy cone-beam CT provided by an embodiment of the present invention.

[0148] The electronic device 500 may include a processor 501, a memory 502, a communication bus 503, and a communication interface 504, and may also include a computer program stored in the memory 502 and executable on the processor 501, such as a material decomposition imaging program for oral dual-energy cone-beam CT.

[0149] In some embodiments, the processor 501 may be composed of an integrated circuit. The processor 501 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device. It runs or executes programs or modules stored in the memory 502 (for example, executing the material decomposition imaging program of oral dual-energy cone-beam CT, etc.), and calls the data stored in the memory 502 to execute various functions of the electronic device and process data.

[0150] The memory 502 includes at least one type of readable storage medium, which includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. The memory 502 can be used not only to store application software and various data installed in the electronic device, such as the code of the material decomposition imaging program of the oral dual-energy cone-beam CT, but also to temporarily store data that has been output or is to be output.

[0151] The communication bus 503 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 502 and at least one processor 501, etc.

[0152] The communication interface 504 is used for communication between the electronic device and other devices, and includes a network interface and a user interface.

[0153] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0154] For example, although not shown, the electronic device may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 501 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The electronic device may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0155] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0156] Acquire high-energy and low-energy original data acquired by oral dual-energy cone-beam CT, perform projection angle compensation on the high-energy and low-energy original data, and obtain high- and low-energy compensated data;

[0157] Performing three-dimensional reconstruction on the high and low energy compensation data to obtain high and low energy volume attenuation images;

[0158] Performing non-local mean filtering on the high and low energy volume attenuation images to obtain high and low energy volume attenuation filtered images;

[0159] Performing material coefficient decomposition on the high and low energy volume attenuation filter images to obtain decomposition coefficient images;

[0160] A material decomposition image corresponding to the high-energy and low-energy original data is generated according to the decomposition coefficient image.

[0161] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0162] Specifically, the specific implementation method of the processor 501 for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0163] Furthermore, if the module / unit integrated in the electronic device 500 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0164] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A material decomposition imaging method for oral dual-energy cone-beam CT, characterized in that: The method comprises: Acquire high-energy and low-energy original data acquired by oral dual-energy cone-beam CT, perform projection angle compensation on the high-energy and low-energy original data, and obtain high- and low-energy compensated data; Performing three-dimensional reconstruction on the high and low energy compensation data to obtain high and low energy volume attenuation images; Performing non-local mean filtering on the high and low energy volume attenuation images to obtain high and low energy volume attenuation filtered images; Performing material coefficient decomposition on the high and low energy volume attenuation filter images to obtain decomposition coefficient images; A material decomposition image corresponding to the high-energy and low-energy original data is generated according to the decomposition coefficient image.

2. The method for material decomposition imaging of oral dual-energy cone-beam CT according to claim 1, characterized in that: The performing projection angle compensation on the high energy and low energy original data to obtain high and low energy compensated data includes: Performing projection conversion on the high-energy and low-energy original data to obtain high-energy projection data and low-energy projection data; The high energy and low energy raw data are projected and transformed using the following formula: Wherein, p represents high-energy projection data or low-energy projection data, s0 represents the number of incident photons of oral dual-energy cone-beam CT, and s represents the number of outgoing photons in the high-energy or low-energy raw data; Performing three-dimensional reconstruction on the high-energy projection data and the low-energy projection data to obtain a high-energy reconstructed volume image and a low-energy reconstructed volume image; Performing two-dimensional conversion on the high-energy reconstructed volume image and the low-energy reconstructed volume image to obtain a high-energy forward projection image and a low-energy forward projection image; Performing angle compensation on the high-energy and low-energy original data according to the high-energy forward projection image and the low-energy forward projection image to obtain high- and low-energy compensated data; The high energy and low energy raw data are angle compensated using the following formula: Among them, p H represents the low energy compensation data in the high and low energy compensation data, p L represents the high energy compensation data in the high and low energy compensation data, p Hf represents the high energy forward projection image, p Lf represents the low energy forward projection image.

3. The material decomposition imaging method of oral dual-energy cone-beam CT according to claim 1, characterized in that: The three-dimensional reconstruction of the high and low energy compensation data to obtain high and low energy volume attenuation images includes: Performing ramp filtering on the high and low energy compensation data to obtain filtered data; The filtered data is weighted back-projected to obtain high and low energy volume attenuation images.

4. The method for material decomposition imaging of oral dual-energy cone-beam CT according to claim 1, characterized in that: The step of performing non-local mean filtering on the high and low energy volume attenuation images to obtain high and low energy volume attenuation filtered images includes: Traversing the pixel points in the high-energy and low-energy volume attenuation images respectively, and selecting one pixel point at a time as a central pixel point; Initializing a search pixel block and a neighborhood pixel block in the high and low energy volume attenuation images according to the central pixel point; Calculate the local pixel weight of the central pixel according to the search pixel block and the neighborhood pixel block; The pixel local weight of the central pixel is calculated using the following formula: Wherein, m represents the central pixel point, n represents any pixel point in the search pixel block V(m), V(n) represents the neighborhood pixel block formed by the neighborhood of pixel point n, V(m) represents the search pixel block formed by the neighborhood of pixel point m, e represents a natural constant, q represents a preset adjustable control coefficient, and w(m,n) represents the local weight of the pixel corresponding to the central pixel point in the neighborhood pixel block and the search pixel block; Performing weighted averaging on the search pixel block according to the local pixel weight to obtain a target pixel value; The pixel value of the central pixel is replaced by the target pixel value to obtain a high- and low-energy volume attenuation filter image.

5. The method for material decomposition imaging of oral dual-energy cone-beam CT according to claim 4, characterized in that: The step of performing weighted averaging on the search pixel block according to the local pixel weight to obtain a target pixel value includes: The target pixel value is obtained by weighted averaging the search pixel block using the following formula: Among them, v ′ (m) represents the target pixel value of the center pixel m, V(m) represents the search pixel block composed of the neighborhood of pixel m, n represents any pixel in the search pixel block V(m), w(m,n) represents the local pixel weight of the center pixel, and v(m) represents the pixel value of the center pixel m.

6. The method for material decomposition imaging of oral cavity dual-energy cone-beam CT as claimed in claim 1, characterized in that: The step of performing material coefficient decomposition on the high and low energy volume attenuation filter images to obtain decomposition coefficient images includes: Acquire a base material attenuation coefficient corresponding to a preset base material, and construct a decomposition equation group according to the base material attenuation coefficient and the high and low energy volume attenuation filter images; The decomposed equations are expressed as: Among them, μ h , μ l respectively represent the high-energy volume attenuation image and the low-energy volume attenuation image in the high-energy and low-energy volume attenuation images, μ 1l represent the mass attenuation coefficient of the first base material under high energy conditions and low energy conditions in the base material attenuation coefficient, respectively, μ 2l Respectively represent the mass attenuation coefficient of the second base material under high energy conditions and low energy conditions in the base material attenuation coefficient, ρ1 and ρ2 respectively represent the density values ​​of the first base material and the second base material in the base material attenuation coefficient, and A1 and A2 respectively represent the decomposition coefficient images corresponding to the first base material and the second base material; The decomposition coefficient image corresponding to the base material is solved according to the decomposition equation group.

7. The material decomposition imaging method of oral dual-energy cone-beam CT according to claim 1, characterized in that: Generating the material decomposition images corresponding to the high-energy and low-energy original data according to the decomposition coefficient images includes: The material decomposition images corresponding to the high-energy and low-energy raw data are generated using the following formula: d D =A1μ 1D +A2m 2D s d =A1σ d1 +A2σ d2 Among them, δ D represents the virtual monoenergetic image at the single energy level D in the material decomposition image, A1 and A2 represent the decomposition coefficient images of the first basis material and the second basis material corresponding to the decomposition coefficient image, respectively, μ 1D , μ 2D They represent the attenuation coefficients of the first basis material and the second basis material corresponding to the decomposition coefficient image at a single energy level D, σ d represents the electron density image at a single energy level d in the decomposition image of the substance, σ d1 , σ d2 They respectively represent the electron density values ​​of the first basis material and the second basis material corresponding to the decomposition coefficient image at a single energy level d.

8. A material decomposition imaging device for oral dual-energy cone-beam CT, characterized in that: The device comprises: A projection angle compensation module is used to obtain high-energy and low-energy original data collected by oral dual-energy cone-beam CT, perform projection angle compensation on the high-energy and low-energy original data, and obtain high- and low-energy compensated data; A three-dimensional reconstruction module, used for performing three-dimensional reconstruction on the high and low energy compensation data to obtain high and low energy volume attenuation images; A non-local mean filtering module, used for performing non-local mean filtering on the high and low energy volume attenuation images to obtain high and low energy volume attenuation filtered images; A material coefficient decomposition module, used for performing material coefficient decomposition on the high and low energy volume attenuation filter image to obtain a decomposition coefficient image; The material decomposition image generation module is used to generate the material decomposition images corresponding to the high-energy and low-energy original data according to the decomposition coefficient image.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the material decomposition imaging method of oral dual-energy cone-beam CT as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the material decomposition imaging method of oral dual-energy cone-beam CT according to any one of claims 1 to 7 is implemented.

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